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Alamoodi AH, Albahri OS, Zaidan AA, Alsattar HA, Zaidan BB, Albahri AS, Ismail AR, Kou G, Alzubaidi L, Talal M. Intelligent Emotion and Sensory Remote Prioritisation for Patients with Multiple Chronic Diseases. Sensors (Basel) 2023; 23:1854. [PMID: 36850457 PMCID: PMC9959399 DOI: 10.3390/s23041854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 01/20/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
An intelligent remote prioritization for patients with high-risk multiple chronic diseases is proposed in this research, based on emotion and sensory measurements and multi-criteria decision making. The methodology comprises two phases: (1) a case study is discussed through the adoption of a multi-criteria decision matrix for high-risk level patients; (2) the technique for reorganizing opinion order to interval levels (TROOIL) is modified by combining it with an extended fuzzy-weighted zero-inconsistency (FWZIC) method over fractional orthotriple fuzzy sets to address objective weighting issues associated with the original TROOIL. In the first hierarchy level, chronic heart disease is identified as the most important criterion, followed by emotion-based criteria in the second. The third hierarchy level shows that Peaks is identified as the most important sensor-based criterion and chest pain as the most important emotion criterion. Low blood pressure disease is identified as the most important criterion for patient prioritization, with the most severe cases being prioritized. The results are evaluated using systematic ranking and sensitivity analysis.
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Affiliation(s)
- A. H. Alamoodi
- Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Tanjong Malim 35900, Perak, Malaysia
| | - O. S. Albahri
- Computer Techniques Engineering Department, Mazaya University College, Nassiriya 12733, Thi-Qar, Iraq
| | - A. A. Zaidan
- SP Jain School of Global Management, Lidcombe, Sydney, NSW 2141, Australia
| | - H. A. Alsattar
- Department of Business Administration, College of Administrative Science, The University of Mashreq, Baghdad 10021, Iraq
| | - B. B. Zaidan
- Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
| | - A. S. Albahri
- Iraqi Commission for Computers and Informatics (ICCI), Baghdad 10022, Iraq
| | - Amelia Ritahani Ismail
- Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia
| | - Gang Kou
- School of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, No. 555, Liutai Road, Wenjiang District, Chengdu 611130, China
| | - Laith Alzubaidi
- School of Mechanical, Medical, and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia
- ARC Industrial Transformation Training Centre—Joint Biomechanics, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Mohammed Talal
- Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat 86400, Malaysia
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Alamoodi AH, Zaidan BB, Albahri OS, Garfan S, Ahmaro IYY, Mohammed RT, Zaidan AA, Ismail AR, Albahri AS, Momani F, Al-Samarraay MS, Jasim AN, R.Q.Malik. Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions. COMPLEX INTELL SYST 2023; 9:1-27. [PMID: 36777815 PMCID: PMC9895977 DOI: 10.1007/s40747-023-00972-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 01/01/2023] [Indexed: 02/05/2023]
Abstract
When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic's main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID-19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters.
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Affiliation(s)
- A. H. Alamoodi
- Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - B. B. Zaidan
- Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, Yunlin 64002 Taiwan, ROC
| | - O. S. Albahri
- Computer Techniques Engineering Department, Mazaya University College, Nasiriyah, Iraq
| | - Salem Garfan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
| | - Ibraheem Y. Y. Ahmaro
- Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine
| | - R. T. Mohammed
- Department of Computing Science, Komar University of Science and Technology (KUST), Sulaymaniyah, Iraq
| | - A. A. Zaidan
- SP Jain School of Global Management, Sydney, Australia
| | - Amelia Ritahani Ismail
- Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia
| | - A. S. Albahri
- Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - Fayiz Momani
- E-Business and Commerce Department, Faculty of Administrative and Financial Sciences, University of Petra, Amman, 961343 Jordan
| | - Mohammed S. Al-Samarraay
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
| | | | - R.Q.Malik
- Medical Intrumentation Techniques Engineering Department, Al-Mustaqbal University College, Babylon, Iraq
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Albahri AS, Al-qaysi ZT, Alzubaidi L, Alnoor A, Albahri OS, Alamoodi AH, Bakar AA. A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology. Int J Telemed Appl 2023; 2023:7741735. [PMID: 37168809 PMCID: PMC10164869 DOI: 10.1155/2023/7741735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 02/01/2023] [Accepted: 03/16/2023] [Indexed: 05/13/2023] Open
Abstract
The significance of deep learning techniques in relation to steady-state visually evoked potential- (SSVEP-) based brain-computer interface (BCI) applications is assessed through a systematic review. Three reliable databases, PubMed, ScienceDirect, and IEEE, were considered to gather relevant scientific and theoretical articles. Initially, 125 papers were found between 2010 and 2021 related to this integrated research field. After the filtering process, only 30 articles were identified and classified into five categories based on their type of deep learning methods. The first category, convolutional neural network (CNN), accounts for 70% (n = 21/30). The second category, recurrent neural network (RNN), accounts for 10% (n = 3/30). The third and fourth categories, deep neural network (DNN) and long short-term memory (LSTM), account for 6% (n = 30). The fifth category, restricted Boltzmann machine (RBM), accounts for 3% (n = 1/30). The literature's findings in terms of the main aspects identified in existing applications of deep learning pattern recognition techniques in SSVEP-based BCI, such as feature extraction, classification, activation functions, validation methods, and achieved classification accuracies, are examined. A comprehensive mapping analysis was also conducted, which identified six categories. Current challenges of ensuring trustworthy deep learning in SSVEP-based BCI applications were discussed, and recommendations were provided to researchers and developers. The study critically reviews the current unsolved issues of SSVEP-based BCI applications in terms of development challenges based on deep learning techniques and selection challenges based on multicriteria decision-making (MCDM). A trust proposal solution is presented with three methodology phases for evaluating and benchmarking SSVEP-based BCI applications using fuzzy decision-making techniques. Valuable insights and recommendations for researchers and developers in the SSVEP-based BCI and deep learning are provided.
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Affiliation(s)
- A. S. Albahri
- Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - Z. T. Al-qaysi
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit, Iraq
| | - Laith Alzubaidi
- School of Mechanical, Medical, and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia
- ARC Industrial Transformation Training Centre—Joint Biomechanics, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | | | - O. S. Albahri
- Computer Techniques Engineering Department, Mazaya University College, Nasiriyah, Iraq
- Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia
| | - A. H. Alamoodi
- Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
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Albahri AS, Hamid RA, Zaidan AA, Albahri OS. Early automated prediction model for the diagnosis and detection of children with autism spectrum disorders based on effective sociodemographic and family characteristic features. Neural Comput Appl 2022. [DOI: 10.1007/s00521-022-07822-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Alamleh A, Albahri OS, Zaidan AA, Albahri AS, Alamoodi AH, Zaidan BB, Qahtan S, Alsatar HA, Al-Samarraay MS, Jasim AN. Federated Learning for IoMT Applications: A Standardisation and Benchmarking Framework of Intrusion Detection Systems. IEEE J Biomed Health Inform 2022; 27:878-887. [PMID: 35417360 DOI: 10.1109/jbhi.2022.3167256] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Efficient evaluation for machine learning (ML)-based intrusion detection systems (IDSs) for federated learning (FL) in the Internet of Medical Things (IoMTs) environment falls under the standardisation and multicriteria decision-making (MCDM) problems. Thus, this study is developing an MCDM framework for standardising and benchmarking the ML-based IDSs used in the FL architecture of IoMT applications. In the methodology, firstly, the evaluation criteria of ML-based IDSs are standardised using the fuzzy Delphi method (FDM). Secondly, the evaluation decision matrix (DM) is formulated based on the intersection of standardised evaluation criteria and a list of ML-based IDSs. Such formulation is achieved using a dataset with 125,973 records, and each record comprises 41 features. Thirdly, the integration of MCDM methods is formulated to determine the importance weights of the main and sub standardised security and performance criteria, followed by benchmarking and selecting the optimal ML-based IDSs. In this phase, the Borda voting method is used to unify the different ranks and perform a group benchmarking context. The following results are confirmed. (1) Using FDM, 17 out of 20 evaluation criteria (14 for security and 3 for performance) reach the consensus of experts. (2) The area under curve criterion has the lowest set of weights, whilst the CPU time criterion has the highest one. (3) VIKOR group ranking shows that the BayesNet is a best classifier, whilst SVM is the last choice. For evaluation, three assessments, namely, systematic ranking, computational cost and comparative analysis, are used.
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Albahri AS, Albahri OS, Zaidan AA, Alnoor A, Alsattar HA, Mohammed R, Alamoodi AH, Zaidan BB, Aickelin U, Alazab M, Garfan S, Ahmaro IYY, Ahmed MA. Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: A distribution case study of COVID-19 vaccine doses. Comput Stand Interfaces 2022; 80:103572. [PMID: 34456503 PMCID: PMC8386109 DOI: 10.1016/j.csi.2021.103572] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 08/14/2021] [Accepted: 08/22/2021] [Indexed: 05/26/2023]
Abstract
Owing to the limitations of Pythagorean fuzzy and intuitionistic fuzzy sets, scientists have developed a distinct and successive fuzzy set called the q-rung orthopair fuzzy set (q-ROFS), which eliminates restrictions encountered by decision-makers in multicriteria decision making (MCDM) methods and facilitates the representation of complex uncertain information in real-world circumstances. Given its advantages and flexibility, this study has extended two considerable MCDM methods the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) under the fuzzy environment of q-ROFS. The extensions were called q-rung orthopair fuzzy-weighted zero-inconsistency (q-ROFWZIC) method and q-rung orthopair fuzzy decision by opinion score method (q-ROFDOSM). The methodology formulated had two phases. The first phase 'development' presented the sequential steps of each method thoroughly.The q-ROFWZIC method was formulated and used in determining the weights of evaluation criteria and then integrated into the q-ROFDOSM for the prioritisation of alternatives on the basis of the weighted criteria. In the second phase, a case study regarding the MCDM problem of coronavirus disease 2019 (COVID-19) vaccine distribution was performed. The purpose was to provide fair allocation of COVID-19 vaccine doses. A decision matrix based on an intersection of 'recipients list' and 'COVID-19 distribution criteria' was adopted. The proposed methods were evaluated according to systematic ranking assessment and sensitivity analysis, which revealed that the ranking was subject to a systematic ranking that is supported by high correlation results over different scenarios with variations in the weights of criteria.
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Affiliation(s)
- A S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - Alhamzah Alnoor
- School of Management, Universiti Sains Malaysia, Pulau Pinang, Malaysia
| | - H A Alsattar
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - Rawia Mohammed
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - A H Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - B B Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - Uwe Aickelin
- School of Computing and Information Systems, University of Melbourne, 700 Swanston Street, Victoria 3010 Australia
| | - Mamoun Alazab
- College of Engineering, IT and Environment, Charles Darwin University, NT, Australia
| | - Salem Garfan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - Ibraheem Y Y Ahmaro
- Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine
| | - M A Ahmed
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit, Iraq
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Alamoodi AH, Mohammed RT, Albahri OS, Qahtan S, Zaidan AA, Alsattar HA, Albahri AS, Aickelin U, Zaidan BB, Baqer MJ, Jasim AN. Based on neutrosophic fuzzy environment: a new development of FWZIC and FDOSM for benchmarking smart e-tourism applications. COMPLEX INTELL SYST 2022. [DOI: 10.1007/s40747-022-00689-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
AbstractThe task of benchmarking smart e-tourism applications based on multiple smart key concept attributes is considered a multi-attribute decision-making (MADM) problem. Although the literature review has evaluated and benchmarked these applications, data ambiguity and vagueness continue to be unresolved issues. The robustness of the fuzzy decision by opinion score method (FDOSM) and fuzzy weighted with zero inconsistency (FWZIC) is proven compared with that of other MADM methods. Thus, this study extends FDOSM and FWZIC under a new fuzzy environment to address the mentioned issues whilst benchmarking the applications. The neutrosophic fuzzy set is used for this purpose because of its high ability to handle ambiguous and vague information comprehensively. Fundamentally, the proposed methodology comprises two phases. The first phase adopts and describes the decision matrices of the smart e-tourism applications. The second phase presents the proposed framework in two sections. In the first section, the weight of each attribute of smart e-tourism applications is calculated through the neutrosophic FWZIC (NS-FWZIC) method. The second section employs the weights determined by the NS-FWZIC method to benchmark all the applications per each category (tourism marketing and smart-based tourism recommendation system categories) through the neutrosophic FDOSM (NS-FDOSM). Findings reveal that: (1) the NS-FWZIC method effectively weights the applications’ attributes. Real time receives the highest importance weight (0.402), whereas augmented reality has the lowest weight (0.005). The remaining attributes are distributed in between. (2) In the context of group decision-making, NS-FDOSM is used to uniform the variation found in the individual benchmarking results of the applications across all categories. Systematic ranking, sensitivity analysis and comparison analysis assessments are used to evaluate the robustness of the proposed work. Finally, the limitations of this study are discussed along with several future directions.
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Alsalem MA, Albahri OS, Zaidan AA, Al-Obaidi JR, Alnoor A, Alamoodi AH, Albahri AS, Zaidan BB, Jumaah FM. Rescuing emergency cases of COVID-19 patients: An intelligent real-time MSC transfusion framework based on multicriteria decision-making methods. APPL INTELL 2022; 52:9676-9700. [PMID: 35035091 PMCID: PMC8741536 DOI: 10.1007/s10489-021-02813-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/23/2021] [Indexed: 12/16/2022]
Abstract
Mesenchymal stem cells (MSCs) have shown promising ability to treat critical cases of coronavirus disease 2019 (COVID-19) by regenerating lung cells and reducing immune system overreaction. However, two main challenges need to be addressed first before MSCs can be efficiently transfused to the most critical cases of COVID-19. First is the selection of suitable MSC sources that can meet the standards of stem cell criteria. Second is differentiating COVID-19 patients into different emergency levels automatically and prioritising them in each emergency level. This study presents an efficient real-time MSC transfusion framework based on multicriteria decision-making(MCDM) methods. In the methodology, the testing phase represents the ability to adhere to plastic surfaces, the upregulation and downregulation of specific surface protein markers and finally the ability to differentiate into different kinds of cells. In the development phase, firstly, two scenarios of an augmented dataset based on the medical perspective are generated to produce 80 patients with different emergency levels. Secondly, an automated triage algorithm based on a formal medical guideline is proposed for real-time monitoring of COVID-19 patients with different emergency levels (i.e. mild, moderate, severe and critical) considering the improvement and deterioration procedures from one level to another. Thirdly, a unique decision matrix for each triage level (except mild) is constructed on the basis of the intersection between the evaluation criteria of each emergency level and list of COVID-19 patients. Thereafter, MCDM methods (i.e. analytic hierarchy process [AHP] and vlsekriterijumska optimizcija i kaompromisno resenje [VIKOR]) are integrated to assign subjective weights for the evaluation criteria within each triage level and then prioritise the COVID-19 patients on the basis of individual and group decision-making(GDM) contexts. Results show that: (1) in both scenarios, the proposed algorithm effectively classified the patients into four emergency levels, including mild, moderate, severe and critical, taking into consideration the improvement and deterioration cases. (2) On the basis of experts’ perspectives, clear differences in most individual prioritisations for patients with different emergency levels in both scenarios were found. (3) In both scenarios, COVID-19 patients were prioritised identically between the internal and external group VIKOR. During the evaluation, the statistical objective method indicated that the patient prioritisations underwent systematic ranking. Moreover, comparison analysis with previous work proved the efficiency of the proposed framework. Thus, the real-time MSC transfusion for COVID-19 patients can follow the order achieved in the group VIKOR results.
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Alshammari RFN, Arshad H, Rahman AHA, Albahri OS. Robotics Utilization in Automatic Vision-Based Assessment Systems From Artificial Intelligence Perspective: A Systematic Review. IEEE Access 2022; 10:77537-77570. [DOI: 10.1109/access.2022.3188264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Affiliation(s)
| | - Haslina Arshad
- Institute of IR4.0, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia
| | - Abdul Hadi Abd Rahman
- Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia
| | - O. S. Albahri
- Computer Techniques Engineering Department, Mazaya University College, Nasiriyah, Iraq
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Alamoodi AH, Zaidan BB, Al-Masawa M, Taresh SM, Noman S, Ahmaro IYY, Garfan S, Chen J, Ahmed MA, Zaidan AA, Albahri OS, Aickelin U, Thamir NN, Fadhil JA, Salahaldin A. Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy. Comput Biol Med 2021; 139:104957. [PMID: 34735945 PMCID: PMC8520445 DOI: 10.1016/j.compbiomed.2021.104957] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 10/15/2021] [Accepted: 10/15/2021] [Indexed: 01/04/2023]
Abstract
A substantial impediment to widespread Coronavirus disease (COVID-19) vaccination is vaccine hesitancy. Many researchers across scientific disciplines have presented countless studies in favor of COVID-19 vaccination, but misinformation on social media could hinder vaccination efforts and increase vaccine hesitancy. Nevertheless, studying people's perceptions on social media to understand their sentiment presents a powerful medium for researchers to identify the causes of vaccine hesitancy and therefore develop appropriate public health messages and interventions. To the best of the authors' knowledge, previous studies have presented vaccine hesitancy in specific cases or within one scientific discipline (i.e., social, medical, and technological). No previous study has presented findings via sentiment analysis for multiple scientific disciplines as follows: (1) social, (2) medical, public health, and (3) technology sciences. Therefore, this research aimed to review and analyze articles related to different vaccine hesitancy cases in the last 11 years and understand the application of sentiment analysis on the most important literature findings. Articles were systematically searched in Web of Science, Scopus, PubMed, IEEEXplore, ScienceDirect, and Ovid from January 1, 2010, to July 2021. A total of 30 articles were selected on the basis of inclusion and exclusion criteria. These articles were formed into a taxonomy of literature, along with challenges, motivations, and recommendations for social, medical, and public health and technology sciences. Significant patterns were identified, and opportunities were promoted towards the understanding of this phenomenon.
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Affiliation(s)
- A H Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia.
| | - B B Zaidan
- Future Technology Research Center, College of Future, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, ROC
| | - Maimonah Al-Masawa
- Centre for Tissue Engineering and Regenerative Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latif, 56000, Kuala Lumpur, Malaysia
| | - Sahar M Taresh
- Department of Kindergarten Educational Psychology, Taiz University, Yemen
| | - Sarah Noman
- Department of Community Health, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Malaysia
| | - Ibraheem Y Y Ahmaro
- Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine
| | - Salem Garfan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - Juliana Chen
- The University of Sydney, Charles Perkins Centre, Discipline of Nutrition and Dietetics, School of Life and Environmental Sciences, Camperdown, New South Wales, Australia; Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Australia; Healthy Weight Clinic, MQ Health, Macquarie University Hospital, Australia
| | - M A Ahmed
- Computer Science and Mathematics College, Tikrit University, Iraq
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - Uwe Aickelin
- School of Computing and Information Systems, University of Melbourne, 700 Swanston Street, Victoria, 3010, Australia
| | - Noor N Thamir
- Department of Computer Science, University of Baghdad, Iraq
| | - Julanar Ahmed Fadhil
- Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), 43400 Serdang, Malaysia
| | - Asmaa Salahaldin
- College of Graduate Studies, Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia
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Garfan S, Alamoodi AH, Zaidan BB, Al-Zobbi M, Hamid RA, Alwan JK, Ahmaro IYY, Khalid ET, Jumaah FM, Albahri OS, Zaidan AA, Albahri AS, Al-Qaysi ZT, Ahmed MA, Shuwandy ML, Salih MM, Zughoul O, Mohammed KI, Momani F. Telehealth utilization during the Covid-19 pandemic: A systematic review. Comput Biol Med 2021; 138:104878. [PMID: 34592585 PMCID: PMC8450049 DOI: 10.1016/j.compbiomed.2021.104878] [Citation(s) in RCA: 151] [Impact Index Per Article: 50.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 09/13/2021] [Accepted: 09/13/2021] [Indexed: 12/27/2022]
Abstract
During the coronavirus disease (COVID-19) pandemic, different technologies, including telehealth, are maximised to mitigate the risks and consequences of the disease. Telehealth has been widely utilised because of its usability and safety in providing healthcare services during the COVID-19 pandemic. However, a systematic literature review which provides extensive evidence on the impact of COVID-19 through telehealth and which covers multiple directions in a large-scale research remains lacking. This study aims to review telehealth literature comprehensively since the pandemic started. It also aims to map the research landscape into a coherent taxonomy and characterise this emerging field in terms of motivations, open challenges and recommendations. Articles related to telehealth during the COVID-19 pandemic were systematically searched in the WOS, IEEE, Science Direct, Springer and Scopus databases. The final set included (n = 86) articles discussing telehealth applications with respect to (i) control (n = 25), (ii) technology (n = 14) and (iii) medical procedure (n = 47). Since the beginning of the pandemic, telehealth has been presented in diverse cases. However, it still warrants further attention. Regardless of category, the articles focused on the challenges which hinder the maximisation of telehealth in such times and how to address them. With the rapid increase in the utilization of telehealth in different specialised hospitals and clinics, a potential framework which reflects the authors' implications of the future application and opportunities of telehealth has been established. This article improves our understanding and reveals the full potential of telehealth during these difficult times and beyond.
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Affiliation(s)
- Salem Garfan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - A H Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia.
| | - B B Zaidan
- Future Technology Research Centre, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan, ROC
| | | | - Rula A Hamid
- College of Business Informatics, University of Information Technology and Communications (UOITC), Baghdad, Iraq
| | - Jwan K Alwan
- Biomedical Informatics College, University of Information Technology and Communications (UOITC), Baghdad, Iraq; Faculty of Computer Science and Information Technology, University of Malaya (UM), Malaysia
| | - Ibraheem Y Y Ahmaro
- Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine
| | - Eman Thabet Khalid
- Department of Computer Sciences, College of Education for Pure Sciences, University of Basrah, Basrah, Iraq
| | - F M Jumaah
- Department of Computer and Software Engineering, Polytechnique Montréal, Canada
| | - O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - A S Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - Z T Al-Qaysi
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Iraq
| | - M A Ahmed
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Iraq
| | - Moceheb Lazam Shuwandy
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Iraq
| | - Mahmood M Salih
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Iraq
| | - Omar Zughoul
- Computer Information System, Ahmed Bin Mohammed Military College, Al Shahaniya, Qatar
| | - K I Mohammed
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
| | - Fayiz Momani
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia
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Alsalem MA, Alsattar HA, Albahri AS, Mohammed RT, Albahri OS, Zaidan AA, Alnoor A, Alamoodi AH, Qahtan S, Zaidan BB, Aickelin U, Alazab M, Jumaah FM. Based on T-spherical fuzzy environment: A combination of FWZIC and FDOSM for prioritising COVID-19 vaccine dose recipients. J Infect Public Health 2021; 14:1513-1559. [PMID: 34538731 PMCID: PMC8388152 DOI: 10.1016/j.jiph.2021.08.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 08/14/2021] [Accepted: 08/21/2021] [Indexed: 01/07/2023] Open
Abstract
The problem complexity of multi-criteria decision-making (MCDM) has been raised in the distribution of coronavirus disease 2019 (COVID-19) vaccines, which required solid and robust MCDM methods. Compared with other MCDM methods, the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) have demonstrated their solidity in solving different MCDM challenges. However, the fuzzy sets used in these methods have neglected the refusal concept and limited the restrictions on their constants. To end this, considering the advantage of the T-spherical fuzzy sets (T-SFSs) in handling the uncertainty in the data and obtaining information with more degree of freedom, this study has extended FWZIC and FDOSM methods into the T-SFSs environment (called T-SFWZIC and T-SFDOSM) to be used in the distribution of COVID-19 vaccines. The methodology was formulated on the basis of decision matrix adoption and development phases. The first phase described the adopted decision matrix used in the COVID-19 vaccine distribution. The second phase presented the sequential formulation steps of T-SFWZIC used for weighting the distribution criteria followed by T-SFDOSM utilised for prioritising the vaccine recipients. Results revealed the following: (1) T-SFWZIC effectively weighted the vaccine distribution criteria based on several parameters including T = 2, T = 4, T = 6, T = 8, and T = 10. Amongst all parameters, the age criterion received the highest weight, whereas the geographic locations severity criterion has the lowest weight. (2) According to the T parameters, a considerable variance has occurred on the vaccine recipient orders, indicating that the existence of T values affected the vaccine distribution. (3) In the individual context of T-SFDOSM, no unique prioritisation was observed based on the obtained opinions of each expert. (4) The group context of T-SFDOSM used in the prioritisation of vaccine recipients was considered the final distribution result as it unified the differences found in an individual context. The evaluation was performed based on systematic ranking assessment and sensitivity analysis. This evaluation showed that the prioritisation results based on each T parameter were subject to a systematic ranking that is supported by high correlation results over all discussed scenarios of changing criteria weights values.
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Affiliation(s)
- M A Alsalem
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - H A Alsattar
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - A S Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - R T Mohammed
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia; Faculty of Computing and Innovative Technology, Geomatika University College, Kuala Lumpur, Malaysia
| | - O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia.
| | - Alhamzah Alnoor
- School of Management, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia
| | - A H Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia
| | - Sarah Qahtan
- Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - B B Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim 35900, Malaysia; Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
| | - Uwe Aickelin
- School of Computing and Information Systems, University of Melbourne, 700 Swanston Street, Victoria 3010, Australia
| | - Mamoun Alazab
- College of Engineering, IT and Environment, Charles Darwin University, NT, Australia
| | - F M Jumaah
- Department of Advanced Applications and Embedded Systems, Intel Corporation, Plot 6 Bayan Lepas Technoplex, 11900 Pulau Pinang, Malaysia
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13
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Albahri AS, Zaidan AA, Albahri OS, Zaidan BB, Alamoodi AH, Shareef AH, Alwan JK, Hamid RA, Aljbory MT, Jasim AN, Baqer MJ, Mohammed KI. Development of IoT-based mhealth framework for various cases of heart disease patients. Health Technol 2021. [DOI: 10.1007/s12553-021-00579-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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14
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Alamoodi AH, Zaidan BB, Zaidan AA, Albahri OS, Mohammed KI, Malik RQ, Almahdi EM, Chyad MA, Tareq Z, Albahri AS, Hameed H, Alaa M. Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. Expert Syst Appl 2021; 167:114155. [PMID: 33139966 PMCID: PMC7591875 DOI: 10.1016/j.eswa.2020.114155] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 10/23/2020] [Accepted: 10/23/2020] [Indexed: 05/05/2023]
Abstract
The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 occurred unexpectedly in China in December 2019. Tens of millions of confirmed cases and more than hundreds of thousands of confirmed deaths are reported worldwide according to the World Health Organisation. News about the virus is spreading all over social media websites. Consequently, these social media outlets are experiencing and presenting different views, opinions and emotions during various outbreak-related incidents. For computer scientists and researchers, big data are valuable assets for understanding people's sentiments regarding current events, especially those related to the pandemic. Therefore, analysing these sentiments will yield remarkable findings. To the best of our knowledge, previous related studies have focused on one kind of infectious disease. No previous study has examined multiple diseases via sentiment analysis. Accordingly, this research aimed to review and analyse articles about the occurrence of different types of infectious diseases, such as epidemics, pandemics, viruses or outbreaks, during the last 10 years, understand the application of sentiment analysis and obtain the most important literature findings. Articles on related topics were systematically searched in five major databases, namely, ScienceDirect, PubMed, Web of Science, IEEE Xplore and Scopus, from 1 January 2010 to 30 June 2020. These indices were considered sufficiently extensive and reliable to cover our scope of the literature. Articles were selected based on our inclusion and exclusion criteria for the systematic review, with a total of n = 28 articles selected. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature in accordance with four main categories: lexicon-based models, machine learning-based models, hybrid-based models and individuals. The obtained articles were categorised into motivations related to disease mitigation, data analysis and challenges faced by researchers with respect to data, social media platforms and community. Other aspects, such as the protocol being followed by the systematic review and demographic statistics of the literature distribution, were included in the review. Interesting patterns were observed in the literature, and the identified articles were grouped accordingly. This study emphasised the current standpoint and opportunities for research in this area and promoted additional efforts towards the understanding of this research field.
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Affiliation(s)
- A H Alamoodi
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
| | - B B Zaidan
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
- Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, ROC
| | - A A Zaidan
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
| | - O S Albahri
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
| | - K I Mohammed
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
| | - R Q Malik
- Department of Engineering Technology, Universiti Tun Hussein Onn (UTHM), Batu Pahat, Malaysia
| | - E M Almahdi
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
| | - M A Chyad
- Department of Computing, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
| | - Z Tareq
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit 34001, Iraq
| | - A S Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - Hamsa Hameed
- Faculty of Human Development, Sultan Idris University of Education (UPSI), Tanjung Malim, Malaysia
| | - Musaab Alaa
- Faculty of Languages and Communication, Sultan Idris University of Education (UPSI), Tanjong Malim, Malaysia
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15
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Mohsin AH, Zaidan AA, Zaidan BB, Mohammed KI, Albahri OS, Albahri AS, Alsalem MA. PSO-Blockchain-based image steganography: towards a new method to secure updating and sharing COVID-19 data in decentralised hospitals intelligence architecture. Multimed Tools Appl 2021; 80:14137-14161. [PMID: 33519293 PMCID: PMC7821848 DOI: 10.1007/s11042-020-10284-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/17/2020] [Accepted: 12/22/2020] [Indexed: 05/02/2023]
Abstract
Secure updating and sharing for large amounts of healthcare information (such as medical data on coronavirus disease 2019 [COVID-19]) in efficient and secure transmission are important but challenging in communication channels amongst hospitals. In particular, in addressing the above challenges, two issues are faced, namely, those related to confidentiality and integrity of their health data and to network failure that may cause concerns about data availability. To the authors' knowledge, no study provides secure updating and sharing solution for large amounts of healthcare information in communication channels amongst hospitals. Therefore, this study proposes and discusses a novel steganography-based blockchain method in the spatial domain as a solution. The novelty of the proposed method is the removal and addition of new particles in the particle swarm optimisation (PSO) algorithm. In addition, hash function can hide secret medical COVID-19 data in hospital databases whilst providing confidentiality with high embedding capacity and high image quality. Moreover, stego images with hash data and blockchain technology are used in updating and sharing medical COVID-19 data between hospitals in the network to improve the level of confidentiality and protect the integrity of medical COVID-19 data in grey-scale images, achieve data availability if any connection failure occurs in a single point of the network and eliminate the central point (third party) in the network during transmission. The proposed method is discussed in three stages. Firstly, the pre-hiding stage estimates the embedding capacity of each host image. Secondly, the secret COVID-19 data hiding stage uses PSO algorithm and hash function. Thirdly, the transmission stage transfers the stego images based on blockchain technology and updates all nodes (hospitals) in the network. As proof of concept for the case study, the authors adopted the latest COVID-19 research published in the Computer Methods and Programs in Biomedicine journal, which presents a rescue framework within hospitals for the storage and transfusion of the best convalescent plasma to the most critical patients with COVID-19 on the basis of biological requirements. The validation and evaluation of the proposed method are discussed.
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Affiliation(s)
- A. H. Mohsin
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
- Republic of Iraq-Presidency of Ministries - Establishment of Martyrs, Baghdad, Iraq
| | - A. A. Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
| | - B. B. Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
| | - K. I. Mohammed
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
| | - O. S. Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
| | - A. S. Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - M. A. Alsalem
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak Malaysia
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16
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Mohammed TJ, Albahri AS, Zaidan AA, Albahri OS, Al-Obaidi JR, Zaidan BB, Larbani M, Mohammed RT, Hadi SM. Convalescent-plasma-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on AHP-group TOPSIS and matching component. APPL INTELL 2021; 51:2956-2987. [PMID: 34764579 PMCID: PMC7820530 DOI: 10.1007/s10489-020-02169-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2020] [Indexed: 01/31/2023]
Abstract
As coronavirus disease 2019 (COVID-19) spreads across the world, the transfusion of efficient convalescent plasma (CP) to the most critical patients can be the primary approach to preventing the virus spread and treating the disease, and this strategy is considered as an intelligent computing concern. In providing an automated intelligent computing solution to select the appropriate CP for the most critical patients with COVID-19, two challenges aspects are bound to be faced: (1) distributed hospital management aspects (including scalability and management issues for prioritising COVID-19 patients and donors simultaneously), and (2) technical aspects (including the lack of COVID-19 dataset availability of patients and donors and an accurate matching process amongst them considering all blood types). Based on previous reports, no study has provided a solution for CP-transfusion-rescue intelligent framework during this pandemic that has addressed said challenges and issues. This study aimed to propose a novel CP-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on the matching component process to provide an efficient CP from eligible donors to the most critical patients using multicriteria decision-making (MCDM) methods. A dataset, including COVID-19 patients/donors that have met the important criteria in the virology field, must be augmented to improve the developed framework. Four consecutive phases conclude the methodology. In the first phase, a new COVID-19 dataset is generated on the basis of medical-reference ranges by specialised experts in the virology field. The simulation data are classified into 80 patients and 80 donors on the basis of the five biomarker criteria with four blood types (i.e., A, B, AB, and O) and produced for COVID-19 case study. In the second phase, the identification scenario of patient/donor distributions across four centralised/decentralised telemedicine hospitals is identified 'as a proof of concept'. In the third phase, three stages are conducted to develop a CP-transfusion-rescue framework. In the first stage, two decision matrices are adopted and developed on the basis of the five 'serological/protein biomarker' criteria for the prioritisation of patient/donor lists. In the second stage, MCDM techniques are analysed to adopt individual and group decision making based on integrated AHP-TOPSIS as suitable methods. In the third stage, the intelligent matching components amongst patients/donors are developed on the basis of four distinct rules. In the final phase, the guideline of the objective validation steps is reported. The intelligent framework implies the benefits and strength weights of biomarker criteria to the priority configuration results and can obtain efficient CPs for the most critical patients. The execution of matching components possesses the scalability and balancing presentation within centralised/decentralised hospitals. The objective validation results indicate that the ranking is valid.
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Affiliation(s)
- Thura J. Mohammed
- grid.444506.70000 0000 9272 6490Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Malaysia ,Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - A. S. Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - A. A. Zaidan
- grid.444506.70000 0000 9272 6490Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Malaysia
| | - O. S. Albahri
- grid.444506.70000 0000 9272 6490Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Malaysia
| | - Jameel R. Al-Obaidi
- grid.444506.70000 0000 9272 6490Department of Biology, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim, Perak Malaysia
| | - B. B. Zaidan
- grid.444506.70000 0000 9272 6490Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Malaysia
| | - Moussa Larbani
- grid.34428.390000 0004 1936 893XSchool of Mathematics and Statistics, Carleton University, Ottawa, ON Canada
| | - R. T. Mohammed
- grid.11142.370000 0001 2231 800XFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Suha M. Hadi
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
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Albahri AS, Hamid RA, Albahri OS, Zaidan AA. Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy-TOPSIS methods. Artif Intell Med 2020; 111:101983. [PMID: 33461683 PMCID: PMC7647899 DOI: 10.1016/j.artmed.2020.101983] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 10/02/2020] [Accepted: 11/03/2020] [Indexed: 12/19/2022]
Abstract
CONTEXT AND BACKGROUND Corona virus (COVID) has rapidly gained a foothold and caused a global pandemic. Particularists try their best to tackle this global crisis. New challenges outlined from various medical perspectives may require a novel design solution. Asymptomatic COVID-19 carriers show different health conditions and no symptoms; hence, a differentiation process is required to avert the risk of chronic virus carriers. OBJECTIVES Laboratory criteria and patient dataset are compulsory in constructing a new framework. Prioritisation is a popular topic and a complex issue for patients with COVID-19, especially for asymptomatic carriers due to multi-laboratory criteria, criterion importance and trade-off amongst these criteria. This study presents new integrated decision-making framework that handles the prioritisation of patients with COVID-19 and can detect the health conditions of asymptomatic carriers. METHODS The methodology includes four phases. Firstly, eight important laboratory criteria are chosen using two feature selection approaches. Real and simulation datasets from various medical perspectives are integrated to produce a new dataset involving 56 patients with different health conditions and can be used to check asymptomatic cases that can be detected within the prioritisation configuration. The first phase aims to develop a new decision matrix depending on the intersection between 'multi-laboratory criteria' and 'COVID-19 patient list'. In the second phase, entropy is utilised to set the objective weight, and TOPSIS is adapted to prioritise patients in the third phase. Finally, objective validation is performed. RESULTS The patients are prioritised based on the selected criteria in descending order of health situation starting from the worst to the best. The proposed framework can discriminate among mild, serious and critical conditions and put patients in a queue while considering asymptomatic carriers. Validation findings revealed that the patients are classified into four equal groups and showed significant differences in their scores, indicating the validity of ranking. CONCLUSIONS This study implies and discusses the numerous benefits of the suggested framework in detecting/recognising the health condition of patients prior to discharge, supporting the hospitalisation characteristics, managing patient care and optimising clinical prediction rule.
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Affiliation(s)
- A S Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq.
| | - Rula A Hamid
- College of Business Informatics, University of Information Technology and Communications (UOITC), Baghdad, Iraq.
| | - O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
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18
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Albahri OS, Al-Obaidi JR, Zaidan AA, Albahri AS, Zaidan BB, Salih MM, Qays A, Dawood KA, Mohammed RT, Abdulkareem KH, Aleesa AM, Alamoodi AH, Chyad MA, Zulkifli CZ. Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Comput Methods Programs Biomed 2020; 196:105617. [PMID: 32593060 PMCID: PMC7305916 DOI: 10.1016/j.cmpb.2020.105617] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 06/16/2020] [Indexed: 05/04/2023]
Abstract
CONTEXT People who have recently recovered from the threat of deteriorating coronavirus disease-2019 (COVID-19) have antibodies to the coronavirus circulating in their blood. Thus, the transfusion of these antibodies to deteriorating patients could theoretically help boost their immune system. Biologically, two challenges need to be surmounted to allow convalescent plasma (CP) transfusion to rescue the most severe COVID-19 patients. First, convalescent subjects must meet donor selection plasma criteria and comply with national health requirements and known standard routine procedures. Second, multi-criteria decision-making (MCDM) problems should be considered in the selection of the most suitable CP and the prioritisation of patients with COVID-19. OBJECTIVE This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods. METHOD The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix. RESULT An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments. DISCUSSION The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.
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Affiliation(s)
- O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia
| | - Jameel R Al-Obaidi
- Department of Biology, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak 35900, Malaysia
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia.
| | - A S Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - B B Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia
| | - Mahmood M Salih
- Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit 34001, Iraq
| | - Abdulhadi Qays
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia
| | - K A Dawood
- Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - R T Mohammed
- Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Karrar Hameed Abdulkareem
- Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia
| | - A M Aleesa
- Faculty of Electronic and Electrical Engineering, Universiti Tun Hussein Onn, Batu Pahat, Johor 86400, Malaysia
| | - A H Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia
| | - M A Chyad
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia
| | - Che Zalina Zulkifli
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan, Tanjung Malim 35900, Malaysia
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Mohammed KI, Zaidan AA, Zaidan BB, Albahri OS, Albahri AS, Alsalem MA, Mohsin AH. Novel technique for reorganisation of opinion order to interval levels for solving several instances representing prioritisation in patients with multiple chronic diseases. Comput Methods Programs Biomed 2020; 185:105151. [PMID: 31710981 DOI: 10.1016/j.cmpb.2019.105151] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 07/20/2019] [Accepted: 10/21/2019] [Indexed: 06/10/2023]
Abstract
CONTEXT Telemedicine has been increasingly used in healthcare to provide services to patients remotely. However, prioritising patients with multiple chronic diseases (MCDs) in telemedicine environment is challenging because it includes decision-making (DM) with regard to the emergency degree of each chronic disease for every patient. OBJECTIVE This paper proposes a novel technique for reorganisation of opinion order to interval levels (TROOIL) to prioritise the patients with MCDs in real-time remote health-monitoring system. METHODS The proposed TROOIL technique comprises six steps for prioritisation of patients with MCDs: (1) conversion of actual data into intervals; (2) rule generation; (3) rule ordering; (4) expert rule validation; (5) data reorganisation; and (6) criteria weighting and ranking alternatives within each rule. The secondary dataset of 500 patients from the most relevant study in a remote prioritisation area was adopted. The dataset contains three diseases, namely, chronic heart disease, high blood pressure (BP) and low BP. RESULTS The proposed TROOIL is an effective technique for prioritising patients with MCDs. In the objective validation, remarkable differences were recognised among the groups' scores, indicating identical ranking results. In the evaluation of issues within all scenarios, the proposed framework has an advantage of 22.95% over the benchmark framework. DISCUSSION Patients with the most severe MCD were treated first on the basis of their highest priority levels. The treatment for patients with less severe cases was delayed more than that for other patients. CONCLUSIONS The proposed TROOIL technique can deal with multiple DM problems in prioritisation of patients with MCDs.
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Affiliation(s)
- K I Mohammed
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
| | - B B Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia.
| | - O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
| | - A S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
| | - M A Alsalem
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
| | - A H Mohsin
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
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Napi NM, Zaidan AA, Zaidan BB, Albahri OS, Alsalem MA, Albahri AS. Medical emergency triage and patient prioritisation in a telemedicine environment: a systematic review. Health Technol 2019. [DOI: 10.1007/s12553-019-00357-w] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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21
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Almahdi EM, Zaidan AA, Zaidan BB, Alsalem MA, Albahri OS, Albahri AS. Mobile Patient Monitoring Systems from a Benchmarking Aspect: Challenges, Open Issues and Recommended Solutions. J Med Syst 2019; 43:207. [PMID: 31144129 DOI: 10.1007/s10916-019-1336-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 05/13/2019] [Indexed: 11/30/2022]
Abstract
This paper presents comprehensive insights into mobile patient monitoring systems (MPMSs) from evaluation and benchmarking aspects on the basis of two critical directions. The current evaluation criteria of MPMSs based on the architectural components of MPMSs and possible solutions are discussed. This review highlights four serious issues, namely, multiple evaluation criteria, criterion importance, unmeasurable criteria and data variation, in MPMS benchmarking. Multicriteria decision-making (MCDM) analysis techniques are proposed as effective solutions to solve these issues from a methodological aspect. This methodological aspect involves a framework for benchmarking MPMSs on the basis of MCDM to rank available MPMSs and select a suitable one. The benchmarking framework is discussed in four steps. Firstly, pre-processing and identification procedures are presented. Secondly, the procedure of weight calculation based on the best-worst method (BWM) is described. Thirdly, the development of a benchmark framework by using the VIKOR method is introduced. Lastly, the proposed framework is validated.
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Affiliation(s)
- E M Almahdi
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M A Alsalem
- College of Administration and Economic, University of Mosul, Mosul, Iraq
| | - O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- College of Engineering, University of Information Technology and Communications, Baghdad, Iraq
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22
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Talal M, Zaidan AA, Zaidan BB, Albahri AS, Alamoodi AH, Albahri OS, Alsalem MA, Lim CK, Tan KL, Shir WL, Mohammed KI. Smart Home-based IoT for Real-time and Secure Remote Health Monitoring of Triage and Priority System using Body Sensors: Multi-driven Systematic Review. J Med Syst 2019; 43:42. [PMID: 30648217 DOI: 10.1007/s10916-019-1158-z] [Citation(s) in RCA: 103] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 01/08/2019] [Indexed: 12/12/2022]
Abstract
The Internet of Things (IoT) has been identified in various applications across different domains, such as in the healthcare sector. IoT has also been recognised for its revolution in reshaping modern healthcare with aspiring wide range prospects, including economical, technological and social. This study aims to establish IoT-based smart home security solutions for real-time health monitoring technologies in telemedicine architecture. A multilayer taxonomy is driven and conducted in this study. In the first layer, a comprehensive analysis on telemedicine, which focuses on the client and server sides, shows that other studies associated with IoT-based smart home applications have several limitations that remain unaddressed. Particularly, remote patient monitoring in healthcare applications presents various facilities and benefits by adopting IoT-based smart home technologies without compromising the security requirements and potentially large number of risks. An extensive search is conducted to identify articles that handle these issues, related applications are comprehensively reviewed and a coherent taxonomy for these articles is established. A total number of (n = 3064) are gathered between 2007 and 2017 for most reliable databases, such as ScienceDirect, Web of Science and Institute of Electrical and Electronic Engineer Xplore databases. Then, the articles based on IoT studies that are associated with telemedicine applications are filtered. Nine articles are selected and classified into two categories. The first category, which accounts for 22.22% (n = 2/9), includes surveys on telemedicine articles and their applications. The second category, which accounts for 77.78% (n = 7/9), includes articles on the client and server sides of telemedicine architecture. The collected studies reveal the essential requirement in constructing another taxonomy layer and review IoT-based smart home security studies. Therefore, IoT-based smart home security features are introduced and analysed in the second layer. The security of smart home design based on IoT applications is an aspect that represents a crucial matter for general occupants of smart homes, in which studies are required to provide a better solution with patient security, privacy protection and security of users' entities from being stolen or compromised. Innovative technologies have dispersed limitations related to this matter. The existing gaps and trends in this area should be investigated to provide valuable visions for technical environments and researchers. Thus, 67 articles are obtained in the second layer of our taxonomy and are classified into six categories. In the first category, 25.37% (n = 17/67) of the articles focus on architecture design. In the second category, 17.91% (n = 12/67) includes security analysis articles that investigate the research status in the security area of IoT-based smart home applications. In the third category, 10.44% (n = 7/67) includes articles about security schemes. In the fourth category, 17.91% (n = 12/67) comprises security examination. In the fifth category, 13.43% (n = 9/67) analyses security protocols. In the final category, 14.92% (n = 10/67) analyses the security framework. Then, the identified basic characteristics of this emerging field are presented and provided in the following aspects. Open challenges experienced on the development of IoT-based smart home security are addressed to be adopted fully in telemedicine applications. Then, the requirements are provided to increase researcher's interest in this study area. On this basis, a number of recommendations for different parties are described to provide insights on the next steps that should be considered to enhance the security of smart homes based on IoT. A map matching for both taxonomies is developed in this study to determine the novel risks and benefits of IoT-based smart home security for real-time remote health monitoring within client and server sides in telemedicine applications.
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Affiliation(s)
- Mohammed Talal
- Department of Communication Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A H Alamoodi
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M A Alsalem
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - C K Lim
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - K L Tan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - W L Shir
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - K I Mohammed
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
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Enaizan O, Zaidan AA, Alwi NHM, Zaidan BB, Alsalem MA, Albahri OS, Albahri AS. Electronic medical record systems: decision support examination framework for individual, security and privacy concerns using multi-perspective analysis. Health Technol 2018. [DOI: 10.1007/s12553-018-0278-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Mohsin AH, Zaidan AA, Zaidan BB, Ariffin SAB, Albahri OS, Albahri AS, Alsalem MA, Mohammed KI, Hashim M. Real-Time Medical Systems Based on Human Biometric Steganography: a Systematic Review. J Med Syst 2018; 42:245. [PMID: 30374820 DOI: 10.1007/s10916-018-1103-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Accepted: 10/09/2018] [Indexed: 11/26/2022]
Abstract
In real-time medical systems, the role of biometric technology is significant in authentication systems because it is used in verifying the identity of people through their biometric features. The biometric technology provides crucial properties for biometric features that can support the process of personal identification. The storage of biometric template within a central database makes it vulnerable to attack which can also occur during data transmission. Therefore, an alternative mechanism of protection becomes important to develop. On this basis, this study focuses on providing a detailed analysis of the extant literature (2013-2018) to identify the taxonomy and research distribution. Furthermore, this study also seeks to ascertain the challenges and motivations associated with biometric steganography in real-time medical systems to provide recommendations that can enhance the efficient use of real-time medical systems in biometric steganography and its applications. A review of articles on human biometric steganography in real-time medical systems obtained from three main databases (IEEE Xplore, ScienceDirect and Web of Science) is conducted according to an appropriate review protocol. Then, 41 related articles are selected by using exclusion and inclusion criteria. Majority of the studies reviewed had been conducted in the field of data-hiding (particularly steganography) technologies. In this review, various steganographic methods that have been applied in different human biometrics are investigated. Thereafter, these methods are categorised according to taxonomy, and the results are presented on the basis of human steganography biometric real-time medical systems, testing and evaluation methods, significance of use and applications and techniques. Finally, recommendations on how the challenges associated with data hiding can be addressed are provided to enhance the efficiency of using biometric information processed in any authentication real-time medical system. These recommendations are expected to be immensely helpful to developers, company users and researchers.
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Affiliation(s)
- A H Mohsin
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | | | - O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M A Alsalem
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - K I Mohammed
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M Hashim
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
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Tariq I, AlSattar HA, Zaidan AA, Zaidan BB, Abu Bakar MR, Mohammed RT, Albahri OS, Alsalem MA, Albahri AS. MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems. Neural Comput Appl 2018. [DOI: 10.1007/s00521-018-3808-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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26
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Mohsin AH, Zaidan AA, Zaidan BB, Albahri AS, Albahri OS, Alsalem MA, Mohammed KI. Real-Time Remote Health Monitoring Systems Using Body Sensor Information and Finger Vein Biometric Verification: A Multi-Layer Systematic Review. J Med Syst 2018; 42:238. [PMID: 30327939 DOI: 10.1007/s10916-018-1104-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 10/09/2018] [Indexed: 10/28/2022]
Abstract
The development of wireless body area sensor networks is imperative for modern telemedicine. However, attackers and cybercriminals are gradually becoming aware in attacking telemedicine systems, and the black market value of protected health information has the highest price nowadays. Security remains a formidable challenge to be resolved. Intelligent home environments make up one of the major application areas of pervasive computing. Security and privacy are the two most important issues in the remote monitoring and control of intelligent home environments for clients and servers in telemedicine architecture. The personal authentication approach that uses the finger vein pattern is a newly investigated biometric technique. This type of biometric has many advantages over other types (explained in detail later on) and is suitable for different human categories and ages. This study aims to establish a secure verification method for real-time monitoring systems to be used for the authentication of patients and other members who are working in telemedicine systems. The process begins with the sensor based on Tiers 1 and 2 (client side) in the telemedicine architecture and ends with patient verification in Tier 3 (server side) via finger vein biometric technology to ensure patient security on both sides. Multilayer taxonomy is conducted in this research to attain the study's goal. In the first layer, real-time remote monitoring studies based on the sensor technology used in telemedicine applications are reviewed and analysed to provide researchers a clear vision of security and privacy based on sensors in telemedicine. An extensive search is conducted to identify articles that deal with security and privacy issues, related applications are reviewed comprehensively and a coherent taxonomy of these articles is established. ScienceDirect, IEEE Xplore and Web of Science databases are checked for articles on mHealth in telemedicine based on sensors. A total of 3064 papers are collected from 2007 to 2017. The retrieved articles are filtered according to the security and privacy of telemedicine applications based on sensors. Nineteen articles are selected and classified into two categories. The first category, which accounts for 57.89% (n = 11/19), includes surveys on telemedicine articles and their applications. The second category, accounting for 42.1% (n = 8/19), includes articles on the three-tiered architecture of telemedicine. The collected studies reveal the essential need to construct another taxonomy layer and review studies on finger vein biometric verification systems. This map-matching for both taxonomies is developed for this study to go deeply into the sensor field and determine novel risks and benefits for patient security and privacy on client and server sides in telemedicine applications. In the second layer of our taxonomy, the literature on finger vein biometric verification systems is analysed and reviewed. In this layer, we obtain a final set of 65 articles classified into four categories. In the first category, 80% (n = 52/65) of the articles focus on development and design. In the second category, 12.30% (n = 8/65) includes evaluation and comparative articles. These articles are not intensively included in our literature analysis. In the third category, 4.61% (n = 3/65) includes articles about analytical studies. In the fourth category, 3.07% (n = 2/65) comprises reviews and surveys. This study aims to provide researchers with an up-to-date overview of studies that have been conducted on (user/patient) authentication to enhance the security level in telemedicine or any information system. In the current study, taxonomy is presented by explaining previous studies. Moreover, this review highlights the motivations, challenges and recommendations related to finger vein biometric verification systems and determines the gaps in this research direction (protection of finger vein templates in real time), which represent a new research direction in this area.
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Affiliation(s)
- A H Mohsin
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M A Alsalem
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - K I Mohammed
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
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Alsalem MA, Zaidan AA, Zaidan BB, Hashim M, Albahri OS, Albahri AS, Hadi A, Mohammed KI. Systematic Review of an Automated Multiclass Detection and Classification System for Acute Leukaemia in Terms of Evaluation and Benchmarking, Open Challenges, Issues and Methodological Aspects. J Med Syst 2018; 42:204. [PMID: 30232632 DOI: 10.1007/s10916-018-1064-9] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 09/06/2018] [Indexed: 10/28/2022]
Abstract
This study aims to systematically review prior research on the evaluation and benchmarking of automated acute leukaemia classification tasks. The review depends on three reliable search engines: ScienceDirect, Web of Science and IEEE Xplore. A research taxonomy developed for the review considers a wide perspective for automated detection and classification of acute leukaemia research and reflects the usage trends in the evaluation criteria in this field. The developed taxonomy consists of three main research directions in this domain. The taxonomy involves two phases. The first phase includes all three research directions. The second one demonstrates all the criteria used for evaluating acute leukaemia classification. The final set of studies includes 83 investigations, most of which focused on enhancing the accuracy and performance of detection and classification through proposed methods or systems. Few efforts were made to undertake the evaluation issues. According to the final set of articles, three groups of articles represented the main research directions in this domain: 56 articles highlighted the proposed methods, 22 articles involved proposals for system development and 5 papers centred on evaluation and comparison. The other taxonomy side included 16 main and sub-evaluation and benchmarking criteria. This review highlights three serious issues in the evaluation and benchmarking of multiclass classification of acute leukaemia, namely, conflicting criteria, evaluation criteria and criteria importance. It also determines the weakness of benchmarking tools. To solve these issues, multicriteria decision-making (MCDM) analysis techniques were proposed as effective recommended solutions in the methodological aspect. This methodological aspect involves a proposed decision support system based on MCDM for evaluation and benchmarking to select suitable multiclass classification models for acute leukaemia. The said support system is examined and has three sequential phases. Phase One presents the identification procedure and process for establishing a decision matrix based on a crossover of evaluation criteria and acute leukaemia multiclass classification models. Phase Two describes the decision matrix development for the selection of acute leukaemia classification models based on the integrated Best and worst method (BWM) and VIKOR. Phase Three entails the validation of the proposed system.
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Affiliation(s)
- M A Alsalem
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M Hashim
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - Ali Hadi
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - K I Mohammed
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
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Albahri OS, Zaidan AA, Zaidan BB, Hashim M, Albahri AS, Alsalem MA. Real-Time Remote Health-Monitoring Systems in a Medical Centre: A Review of the Provision of Healthcare Services-Based Body Sensor Information, Open Challenges and Methodological Aspects. J Med Syst 2018; 42:164. [PMID: 30043085 DOI: 10.1007/s10916-018-1006-6] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2018] [Accepted: 06/21/2018] [Indexed: 01/11/2023]
Abstract
Promoting patient care is a priority for all healthcare providers with the overall purpose of realising a high degree of patient satisfaction. A medical centre server is a remote computer that enables hospitals and physicians to analyse data in real time and offer appropriate services to patients. The server can also manage, organise and support professionals in telemedicine. Therefore, a remote medical centre server plays a crucial role in sustainably delivering quality healthcare services in telemedicine. This article presents a comprehensive review of the provision of healthcare services in telemedicine applications, especially in the medical centre server. Moreover, it highlights the open issues and challenges related to providing healthcare services in the medical centre server within telemedicine. Methodological aspects to control and manage the process of healthcare service provision and three distinct and successive phases are presented. The first phase presents the identification process to propose a decision matrix (DM) on the basis of a crossover of 'multi-healthcare services' and 'hospital list' within intelligent data and service management centre (Tier 4). The second phase discusses the development of a DM for hospital selection on the basis of integrated VIKOR-Analytic Hierarchy Process (AHP) methods. Finally, the last phase examines the validation process for the proposed framework.
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Affiliation(s)
- O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M Hashim
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M A Alsalem
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
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Zaidan AA, Zaidan BB, Albahri OS, Alsalem MA, Albahri AS, Yas QM, Hashim M. A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: coherent taxonomy, open issues and recommendation pathway solution. Health Technol 2018. [DOI: 10.1007/s12553-018-0223-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Albahri OS, Albahri AS, Mohammed KI, Zaidan AA, Zaidan BB, Hashim M, Salman OH. Systematic Review of Real-time Remote Health Monitoring System in Triage and Priority-Based Sensor Technology: Taxonomy, Open Challenges, Motivation and Recommendations. J Med Syst 2018; 42:80. [PMID: 29564649 DOI: 10.1007/s10916-018-0943-4] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 03/15/2018] [Indexed: 11/30/2022]
Abstract
The new and ground-breaking real-time remote monitoring in triage and priority-based sensor technology used in telemedicine have significantly bounded and dispersed communication components. To examine these technologies and provide researchers with a clear vision of this area, we must first be aware of the utilised approaches and existing limitations in this line of research. To this end, an extensive search was conducted to find articles dealing with (a) telemedicine, (b) triage, (c) priority and (d) sensor; (e) comprehensively review related applications and establish the coherent taxonomy of these articles. ScienceDirect, IEEE Xplore and Web of Science databases were checked for articles on triage and priority-based sensor technology in telemedicine. The retrieved articles were filtered according to the type of telemedicine technology explored. A total of 150 articles were selected and classified into two categories. The first category includes reviews and surveys of triage and priority-based sensor technology in telemedicine. The second category includes articles on the three-tiered architecture of telemedicine. Tier 1 represents the users. Sensors acquire the vital signs of the users and send them to Tier 2, which is the personal gateway that uses local area network protocols or wireless body area network. Medical data are sent from Tier 2 to Tier 3, which is the healthcare provider in medical institutes. Then, the motivation for using triage and priority-based sensor technology in telemedicine, the issues related to the obstruction of its application and the development and utilisation of telemedicine are examined on the basis of the findings presented in the literature.
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Affiliation(s)
- O S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - K I Mohammed
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - M Hashim
- Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - Omar H Salman
- Al-Iraqia University, Al Adhmia - HaibaKhaton, Baghdad, Iraq
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Kalid N, Zaidan AA, Zaidan BB, Salman OH, Hashim M, Albahri OS, Albahri AS. Based on Real Time Remote Health Monitoring Systems: A New Approach for Prioritization "Large Scales Data" Patients with Chronic Heart Diseases Using Body Sensors and Communication Technology. J Med Syst 2018; 42:69. [PMID: 29500683 DOI: 10.1007/s10916-018-0916-7] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Accepted: 02/13/2018] [Indexed: 11/24/2022]
Abstract
This paper presents a new approach to prioritize "Large-scale Data" of patients with chronic heart diseases by using body sensors and communication technology during disasters and peak seasons. An evaluation matrix is used for emergency evaluation and large-scale data scoring of patients with chronic heart diseases in telemedicine environment. However, one major problem in the emergency evaluation of these patients is establishing a reasonable threshold for patients with the most and least critical conditions. This threshold can be used to detect the highest and lowest priority levels when all the scores of patients are identical during disasters and peak seasons. A practical study was performed on 500 patients with chronic heart diseases and different symptoms, and their emergency levels were evaluated based on four main measurements: electrocardiogram, oxygen saturation sensor, blood pressure monitoring, and non-sensory measurement tool, namely, text frame. Data alignment was conducted for the raw data and decision-making matrix by converting each extracted feature into an integer. This integer represents their state in the triage level based on medical guidelines to determine the features from different sources in a platform. The patients were then scored based on a decision matrix by using multi-criteria decision-making techniques, namely, integrated multi-layer for analytic hierarchy process (MLAHP) and technique for order performance by similarity to ideal solution (TOPSIS). For subjective validation, cardiologists were consulted to confirm the ranking results. For objective validation, mean ± standard deviation was computed to check the accuracy of the systematic ranking. This study provides scenarios and checklist benchmarking to evaluate the proposed and existing prioritization methods. Experimental results revealed the following. (1) The integration of TOPSIS and MLAHP effectively and systematically solved the patient settings on triage and prioritization problems. (2) In subjective validation, the first five patients assigned to the doctors were the most urgent cases that required the highest priority, whereas the last five patients were the least urgent cases and were given the lowest priority. In objective validation, scores significantly differed between the groups, indicating that the ranking results were identical. (3) For the first, second, and third scenarios, the proposed method exhibited an advantage over the benchmark method with percentages of 40%, 60%, and 100%, respectively. In conclusion, patients with the most and least urgent cases received the highest and lowest priority levels, respectively.
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Affiliation(s)
- Naser Kalid
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A A Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
| | - B B Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - Omar H Salman
- Al- Iraqia University, Al Adhmia, Haiba Khaton, Baghdad, Iraq
| | - M Hashim
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - O S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
| | - A S Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
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