A medical records managing and securing blockchain based system supported by a Genetic Algorithm and Discrete Wavelet Transform

A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine

The unexpected and rapid spread of the COVID-19 pandemic has amplified the acceptance of remote healthcare systems such as telemedicine. Telemedicine effectively provides remote communication, better treatment recommendation, and personalized treatment on demand. It has emerged as the possible future of medicine. From a privacy perspective, secure storage, preservation, and controlled access to health data with consent are the main challenges to the effective deployment of telemedicine. It is paramount to fully overcome these challenges to integrate the telemedicine system into healthcare. In this regard, emerging technologies such as blockchain and federated learning have enormous potential to strengthen the telemedicine system. These technologies help enhance the overall healthcare standard when applied in an integrated way. The primary aim of this study is to perform a systematic literature review of previous research on privacy-preserving methods deployed with blockchain and federated learning for telemedicine. This study provides an in-depth qualitative analysis of relevant studies based on the architecture, privacy mechanisms, and machine learning methods used for data storage, access, and analytics. The survey allows the integration of blockchain and federated learning technologies with suitable privacy techniques to design a secure, trustworthy, and accurate telemedicine model with a privacy guarantee.

Comprehensive review for healthcare data quality challenges in blockchain technology

There are several features inherent in blockchain, including decentralized storage, distributed ledger, immutability, security and authentication, and it has shifted away from the hype to be used practically in different industries, such as in the healthcare sector. The use of blockchain technology has allowed the provision of improved services to industries. The objective of this paper is to demonstrate how the use of blockchain is influenced by data quality issues in the healthcare industry. The article is structured as a systematic literature review study that uses several articles issued in various databases from 2016 onwards. In this review study, 65 articles were chosen and grouped into a single key aspect of the challenge in the healthcare sector. The findings obtained were analyzed based on factors in three domains, classified as issues pertinent to the adoption, operational and technological domains. This review study aims to use the findings to provide support to the practitioners, stakeholders and professionals, whose purpose is to carry out and manage transformation projects pertinent to blockchain in the field of healthcare. In addition, the organizations would be facilitated in their decision-making processes when the potential blockchain users are made to comprehend the implicit factors related to blockchain.

A novel COVID diagnosis and feature extraction based on discrete wavelet model and classification using X-ray and CT images

Recently, the Covid-19 pandemic has affected several lives of people globally, and there is a need for a massive number of screening tests to diagnose the existence of coronavirus. For the medical specialist, detecting COVID-19 cases is a difficult task. There is a need for fast, cheap and accurate diagnostic tools. The chest X-ray and the computerized tomography (CT) play a significant role in the COVID-19 diagnosis. The advancement of deep learning (DL) approaches helps to introduce a COVID diagnosis system to achieve maximum detection rate with minimum time complexity. This research proposed a discrete wavelet optimized network model for COVID-19 diagnosis and feature extraction to overcome these problems. It consists of three stages pre-processing, feature extraction and classification. The raw images are filtered in the pre-processing phase to eliminate unnecessary noises and improve the image quality using the MMG hybrid filtering technique. The next phase is feature extraction, in this stage, the features are extracted, and the dimensionality of the features is diminished with the aid of a modified discrete wavelet based Mobile Net model. The third stage is the classification here, the convolutional Aquila COVID detection network model is developed to classify normal and COVID-19 positive cases from the collected images of the COVID-CT and chest X-ray dataset. Finally, the performance of the proposed model is compared with some of the existing models in terms of accuracy, specificity, sensitivity, precision, f-score, negative predictive value (NPV) and positive predictive value (PPV), respectively. The proposed model achieves the performance of 99%, 100%, 98.5%, and 99.5% for the CT dataset, and the accomplished accuracy, specificity, sensitivity, and precision values of the proposed model for the X-ray dataset are 98%, 99%, 98% and 97% respectively. In addition, the statistical and cross validation analysis is conducted to validate the effectiveness of the proposed model.

A Framework for User-Focused Electronic Health Record System Leveraging Hyperledger Fabric

This research study aims to examine the possibilities of Hyperledger Fabric (HLF) in the healthcare sector. The study addresses the gap in the knowledge base through developing customization techniques to enable the simplicity and efficacy of Electronic Medical Records (EMR) adoption for healthcare industry applications. The focus of this research explores methods of using blockchain technology that prioritise users. The investigation of several concepts used in developing web applications has been determined. The study identified that an open-source project, known as Hyperledger Fabric, can be utilised to construct a novel method of storing EMRs. The framework provides a test network that can be customised to satisfy the need of several projects, including storing medical records. This research additionally outlines the difficulties encountered and problems that need to be resolved before Hyperledger Fabric can be successfully implemented in healthcare systems. Considering all types of blockchains available, the needs are met by Hyperledger Fabric, which offers a distributed and secure environment for healthcare systems. Blockchain has the potential to transform healthcare by putting the patient at the centre of the system and enhancing health data protection and interoperability. Also, by using grant and revoke access mechanisms, patients have complete control over their medical information as well as authorized doctors who are allowed to view records. This functionality is made possible by the chaincode defined in the blockchain platform. The research study has both practitioner and research implications for the development of secure blockchain-based EMRs.

A node selection algorithm with a genetic method based on PBFT in consortium blockchains

Industry and research communities have widely studied Blockchain technology, and the consortium blockchain is currently the most used category with a wide range of applications. However, issues, such as the performance of consensus mechanisms, have become essential constraints on promoting and applying the consortium blockchain. To improve the performance of the consortium blockchain consensus, we use the practical Byzantine fault tolerance (PBFT) consensus widely used in consortium blockchains to reduce the number of consensus nodes to optimize performance. Using the PBFT consensus, we screen high-performance nodes and obtain a reliable and limited number of consensus nodes. We propose a genetic algorithm-based blockchain consensus algorithm improvement scheme, design the fitness function of blockchain nodes and the genetic algorithm to iterate out consensus node groups with excellent indicators continuously, and finally iterate the nodes participating in the consensus. This algorithm can increase the speed and efficiency of the consensus, block generation, and computation. The algorithm in this article is tested on the FISCO BCOS (i.e., a consortium blockchain platform built by the FISCO open-source working group), and controlled experiments and the experimental results illustrate the safety and practicability of the method.

An Efficient Chaos-Based Image Encryption Technique Using Bitplane Decay and Genetic Operators

Social networks have greatly expanded in the last ten years the need for sharing multimedia data. However, on open networks such as the Internet, where security is frequently compromised, it is simple for eavesdroppers to approach the actual contents without much difficulty. Researchers have created a variety of encryption methods to strengthen the security of this transmission and make it difficult for eavesdroppers to get genuine data. However, these conventional approaches increase computing costs and communication overhead and do not offer protection against fresh threats. The problems with current algorithms encourage academics to further investigate the subject and suggest new algorithms that are more effective than current methods, that reduce overhead, and which are equipped with features needed by next-generation multimedia networks. In this paper, a genetic operator-based encryption method for multimedia security is proposed. It has been noted that the proposed algorithm produces improved key strength results. The investigations using attacks on data loss, differential assaults, statistical attacks, and brute force attacks show that the encryption technique suggested has improved security performance. It focuses on two techniques, bitplane slicing and followed by block segmentation and scrambling. The suggested method first divides the plaintext picture into several blocks, which is then followed by block swapping done by the genetic operator used to combine the genetic information of two different images to generate new offspring. The key stream is produced from an iterative chaotic map with infinite collapse (ICMIC). Based on a close-loop modulation coupling (CMC) approach, a three-dimensional hyperchaotic ICMIC modulation map is proposed. By using a hybrid model of multidirectional circular permutation with this map, a brand-new colour image encryption algorithm is created. In this approach, a multidirectional circular permutation is used to disrupt the image's pixel placements, and genetic operations are used to replace the pixel values. According to simulation findings and security research, the technique can fend off brute-force, statistical, differential, known-plaintext, and chosen-plaintext assaults, and has a strong key sensitivity.

Toward a model for assessing smart hospital readiness within the Industry 4.0 paradigm

Purpose

The fourth industrial revolution and digital transformation have caused paradigm changes in the procedures of goods production and services through disruptive technologies, and they have formed new methods for business models. Health and medicine fields have been under the effect of these technology advancements. The concept of smart hospital is formed according to these technological transformations. The aim of this research, other than explanation of smart hospital components, is to present a model for evaluating a hospital readiness for becoming a smart hospital.

Design/methodology/approach

This research is an applied one, and has been carried out in three phases and according to design science research. Based on the previous studies, in the first phase, the components and technologies effecting a smart hospital are recognized. In the second phase, the extracted components are prioritized using type-2 fuzzy analytic hierarchical process based on the opinion of experts; later, the readiness model is designed. In the third phase, the presented model would be tested in a hospital.

Findings

The research results showed that the technologies of internet of things, robotics, artificial intelligence, radio-frequency identification as well as augmented and virtual reality had the most prominence in a smart hospital.

Originality/value

The innovation and originality of the forthcoming research is to explain the concept of smart hospital, to rank its components and to provide a model for evaluating the readiness of smart hospital. Contribution of this research in terms of theory explains the concept of smart hospital and in terms of application presents a model for assessing the readiness of smart hospitals.

A Novel Approach to Skin Lesion Segmentation: Multipath Fusion Model with Fusion Loss

Segmentation of skin lesions plays a very important role in the early detection of skin cancer. However, indistinguishability due to various artifacts such as hair and contrast between normal skin and lesioned skin is an important challenge for specialist dermatologists. Computer-aided diagnostic systems using deep convolutional neural networks are gaining importance in order to cope with difficulties. This study focuses on deep learning-based fusion networks and fusion loss functions. For the automatic segmentation of skin lesions, U-Net (U-Net + ResNet 2D) with 2D residual blocks and 2D volumetric convolutional neural networks were fused for the first time in this study. Also, a new fusion loss function is proposed by combining Dice Loss (DL) and Focal Tversky Loss (FTL) to make the proposed fused model more robust. Of the 2594 image dataset, 20% is reserved for test data and 80% for training data. In test data training, a Jaccard score of 0.837 and a dice score of 0.918 were obtained. The proposed model was also scored on the ISIC 2018 Task 1 test images, whose ground truths were not shared. The proposed model performed well and achieved a Jaccard index of 0.800 and a dice score of 0.880 in the ISIC 2018 Task 1 test set. In addition, it has been observed that the new fused loss function obtained by fusing Focal Tversky Loss and Dice Loss functions in the proposed model increases the robustness of the model in the tests. The proposed new loss function fusion model has outstripped the cutting-edge approaches in the literature.

IoMT-Based Platform for E-Health Monitoring Based on the Blockchain

With the evolution of information technology, the use of internet of things has increased. It affects several areas such as medical field, smart cities, and information systems. In this work, we will use this technological development in the context of health, particularly e-health. We present a platform based on IoMT to allow the monitoring of patient’s health. To meet the constraint of medical secrecy and confidentiality of information, we will use the Blockchain as a secure system. Our system will use the data collected by several smart sensors such as blood pressure, SPO2 concentration, and EEG signals. These encrypted data will be collected by an embedded Raspberry PI 4 platform (working as a smart data relay) before being processed (on a backend server) and then saved in an embedded Blockchain node. The preliminary results show the effectiveness of the proposed platform as a candidate of a low-cost example of secured Electronic Health Record (EHR).

Feature Extraction Approach for Speaker Verification to Support Healthcare System Using Blockchain Security for Data Privacy

Speech is one form of biometric that combines both physiological and behavioral features. It is beneficial for remote-access transactions over telecommunication networks. Presently, this task is the most challenging one for researchers. People’s mental status in the form of emotions is quite complex, and its complexity depends upon internal behavior. Emotion and facial behavior are essential characteristics through which human internal thought can be predicted. Speech is one of the mechanisms through which human’s various internal reflections can be expected and extracted by focusing on the vocal track, the flow of voice, voice frequency, etc. Human voice specimens of different ages can be emotions that can be predicted through a deep learning approach using feature removal behavior prediction that will help build a step intelligent healthcare system strong and provide data to various doctors of medical institutes and hospitals to understand the physiological behavior of humans. Healthcare is a clinical area with data concentrated where many details are accessed, generated, and circulated periodically. Healthcare systems with many existing approaches like tracing and tracking continuously disclose the system’s constraints in controlling patient data privacy and security. In the healthcare system, majority of the work involves swapping or using decisively confidential and personal data. A key issue is the modeling of approaches that guarantee the value of health-related data while protecting privacy and observing high behavioral standards. This will encourage large-scale perception, especially as healthcare information collection is expected to continue far off this current ongoing pandemic. So, the research section is looking for a privacy-preserving, secure, and sustainable system by using a technology called Blockchain. Data related to healthcare and distribution among institutions is a very challenging task. Storage of facts in the centralized form is a targeted choice for cyber hackers and initiates an accordant sight of patients’ facts which will cause a problem in sharing information over a network. So, this research paper’s approach based on Blockchain for sharing sufferer data in a secured manner is presented. Finally, the proposed model for extracting optimum value in error rate and accuracy was analyzed using different feature removal approaches to determine which feature removal performs better with different voice specimen variations. The proposed method increases the rate of correct evidence collection and minimizes the loss and authentication issues and using feature extraction based on text validation increases the sustainability of the healthcare system.

Blockchain technology in healthcare: A systematic review

Blockchain technology (BCT) has emerged in the last decade and added a lot of interest in the healthcare sector. The purpose of this systematic literature review (SLR) is to explore the potential paradigm shift in healthcare utilizing BCT. The study is compiled by reviewing research articles published in nine well-reputed venues such as IEEE Xplore, ACM Digital Library, Springs Link, Scopus, Taylor & Francis, Science Direct, PsycINFO, Ovid Medline, and MDPI between January 2016 to August 2021. A total of 1,192 research studies were identified out of which 51 articles were selected based on inclusion criteria for this SLR that presents the modern information on the recent implications and gaps in the use of BCT for enhancing the healthcare procedures. According to the outcomes, BCT is being applied to design the novel and advanced interventions to enrich the current protocol of managing, distributing, and processing clinical records and personal medical information. BCT is enduring the conceptual development in the healthcare domain, where it has summed up the substantial elements through better and enhanced efficiency, technological innovation, access control, data privacy, and security. A framework is developed to address the probable field where future researchers can add considerable value, such as data protection, system architecture, and regulatory compliance. Finally, this SLR concludes that the upcoming research can support the pervasive implementation of BCT to address the critical dilemmas related to health diagnostics, enhancing the patient healthcare process in remote monitoring or emergencies, data integrity, and avoiding fraud.

Return Rate Prediction in Blockchain Financial Products Using Deep Learning

Recently, bitcoin-based blockchain technologies have received significant interest among investors. They have concentrated on the prediction of return and risk rates of the financial product. So, an automated tool to predict the return rate of bitcoin is needed for financial products. The recently designed machine learning and deep learning models pave the way for the return rate prediction process. In this aspect, this study develops an intelligent return rate predictive approach using deep learning for blockchain financial products (RRP-DLBFP). The proposed RRP-DLBFP technique involves designing a long short-term memory (LSTM) model for the predictive analysis of return rate. In addition, Adam optimizer is applied to optimally adjust the LSTM model’s hyperparameters, consequently increasing the predictive performance. The learning rate of the LSTM model is adjusted using the oppositional glowworm swarm optimization (OGSO) algorithm. The design of the OGSO algorithm to optimize the LSTM hyperparameters for bitcoin return rate prediction shows the novelty of the work. To ensure the supreme performance of the RRP-DLBFP technique, the Ethereum (ETH) return rate is chosen as the target, and the simulation results are investigated in different measures. The simulation outcomes highlighted the supremacy of the RRP-DLBFP technique over the current state of art techniques in terms of diverse evaluation parameters. For the MSE, the proposed RRP-DLBFP has 0.0435 and 0.0655 compared to an average of 0.6139 and 0.723 for compared methods in training and testing, respectively.

Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews

BACKGROUND

The recent, rapid development of digital technologies offers new possibilities for more efficient implementation of electronic health record (EHR) and personal health record (PHR) systems. A growing volume of healthcare data has been the hallmark of this digital transformation. The large healthcare datasets' complexity and their dynamic nature pose various challenges related to processing, analysis, storage, security, privacy, data exchange, and usability.

MATERIALS AND METHODS

We performed a systematic review of systematic reviews to assess technological progress in EHR and PHR systems. We searched MEDLINE, Cochrane, Web of Science, and Scopus for systematic literature reviews on technological advancements that support EHR and PHR systems published between January 1, 2010, and October 06, 2020.

RESULTS

The searches resulted in a total of 2,448 hits. Of these, we finally selected 23 systematic reviews. Most of the included papers dealt with information extraction tools and natural language processing technology (n = 10), followed by studies that assessed the use of blockchain technology in healthcare (n = 8). Other areas of digital technology research included EHR and PHR systems in austere settings (n = 1), de-identification methods (n = 1), visualization techniques (n = 1), communication tools within EHR and PHR systems (n = 1), and methodologies for defining Clinical Information Models that promoted EHRs and PHRs interoperability (n = 1).

CONCLUSIONS

Technological advancements can improve the efficiency in the implementation of EHR and PHR systems in numerous ways. Natural language processing techniques, either rule-based, machine-learning, or deep learning-based, can extract information from clinical narratives and other unstructured data locked in EHRs and PHRs, allowing secondary research (i.e., phenotyping). Moreover, EHRs and PHRs are expected to be the primary beneficiaries of the blockchain technology implementation on Health Information Systems. Governance regulations, lack of trust, poor scalability, security, privacy, low performance, and high cost remain the most critical challenges for implementing these technologies.

BlockPres: A Novel Blockchain-Based Incentive Mechanism to Mitigate Inequalities for Prescription Management System

The study presents a blockchain-based incentive mechanism intended to encourage those in underserved communities to engage with healthcare services. The smart healthcare system, which is the result of the amalgamation of advanced technologies, has emerged recently and is increasingly seen as essential to meet the needs of modern society. An important part of the healthcare system is the prescription management system, but studies show that prescription affordability and accessibility play a part in creating unequal access for underserved communities. This is a form of unequal access that results in those living in underserved communities to become disengaged from accessing healthcare services. In New Zealand, the prescription management system plays a crucial role and this study seeks to address the issue by presenting the BlockPres framework, which uses a novel incentive mechanism to encourage patients to participate and engage with services in order to be rewarded. The blockchain attribute of immutability in BlockPres enhances equality and participation by providing sophisticated authorisation and authentication capabilities for healthcare providers and patients. BlockPres empowers the patient by assigning ownership or control of some patient information to the patient. A simulation is carried out using the Ethereum blockchain and the evaluation of successful transaction completion and superficial performance assessment demonstrates that the blockchain would be sufficient to cope with the needs of a prescription management system. Furthermore, for the simulation, a BlockPres Smart Contract is developed using solidity and implemented in Remix. The Ropsten network is used as the simulation environment and the initial results show that the proposed incentive mechanism mitigates unequal access.

Re-designing the business organization using disruptive innovations based on blockchain-IoT integrated architecture for improving agility in future Industry 4.0

Purpose

Blockchain and Internet of Things (IoT) technologies have recently gained much attention for Industry 4.0. With the emergence of disruptive technologies, it has become essential to redesign the business for innovations based on blockchain–IoT integrated architecture that helps organizations to improve agility in their operations. The paper aims to discuss this issue.

Design/methodology/approach

An industrial pump was Sensorized and IoTized to monitor its operations on real time and take predictive measures for managing these assets with more agility. The developed architecture was further extended for proposing the use of blockchain and how it can benefit the organization.

Findings

The known features of blockchain such as increasing the capacity of decentralization, trust-less transactions, security and allowing autonomous coordination of the devices along with the boons of IoT will help achieve the motto of improving agility in Industry 4.0.

Originality/value

This paper gives a new dimension to utilization of blockchain technology. blockchain along with IoT that gives a way forward for industries like manufacturing, oil and gas, engineering and construction, utilities, etc. to re-designing the business organization in a more agile way.

Data sharing: using blockchain and decentralized data technologies to unlock the potential of artificial intelligence: What can assisted reproduction learn from other areas of medicine?

The extension of blockchain use for nonfinancial domains has revealed opportunities to the health care sector that answer the need for efficient and effective data and information exchanges in a secure and transparent manner. Blockchain is relatively novel in health care and particularly for data analytics, although there are examples of improvements achieved. We provide a systematic review of blockchain uses within the health care industry, with a particular focus on the in vitro fertilization (IVF) field. Blockchain technology in the fertility sector, including data sharing collaborations compliant with ethical data handling within confines of international law, allows for large-scale prospective cohort studies to proceed at an international scale. Other opportunities include gamete donation and matching, consent sharing, and shared resources between different clinics.

A Blockchain-Enabled Framework for mHealth Systems

Presently modern technology makes a significant contribution to the transition from traditional healthcare to smart healthcare systems. Mobile health (mHealth) uses advances in wearable sensors, telecommunications and the Internet of Things (IoT) to propose a new healthcare concept centered on the patient. Patients' real-time remote continuous health monitoring, remote diagnosis, treatment, and therapy is possible in an mHealth system. However, major limitations include the transparency, security, and privacy of health data. One possible solution to this is the use of blockchain technologies, which have found numerous applications in the healthcare domain mainly due to theirs features such as decentralization (no central authority is needed), immutability, traceability, and transparency. We propose an mHealth system that uses a private blockchain based on the Ethereum platform, where wearable sensors can communicate with a smart device (a smartphone or smart tablet) that uses a peer-to-peer hypermedia protocol, the InterPlanetary File System (IPFS), for the distributed storage of health-related data. Smart contracts are used to create data queries, to access patient data by healthcare providers, to record diagnostic, treatment, and therapy, and to send alerts to patients and medical professionals.

A Quantitative and Qualitative Review on the Main Research Streams Regarding Blockchain Technology in Healthcare

(1) Background: Blockchain technology has been gaining high popularity in the healthcare domain. This has brought about a spate of recent studies regarding blockchain technology in healthcare, creating high demand for quantitative or qualitative reviews on the main research streams thereof. In order to contribute to satisfying the high demand, this research presents a quantitative and qualitative review on studies regarding blockchain technology in healthcare. (2) Methods: A quantitative review was performed by searching the Web of Science database for articles published until 10 March in 2020, and a qualitative review was conducted by using the content analysis based on the integrative view of Leavitt’s diamond model. (3) Results: The quantitative review identified five research streams. The number of articles about blockchain technology in healthcare has dramatically increased since 2016, with a compound annual growth rate of 254.4%. English is the most dominant language used in the articles, and the USA and China are the top two countries of origin of the articles, representing overwhelming portions. The IEEE Access, Journal of Medical Systems, Journal of Medical Internet Research, Applied Sciences Basel, and Sensors are the top five journals in terms of publication. The articles showed an L-shaped distribution in terms of their annual average numbers of citations. The qualitative review revealed two research streams. Most of the top 10 articles ranked by their annual average numbers of citations concentrated on developing or proposing new technological solutions using blockchain technology to effectively revolutionize the current methods of managing data in the healthcare domain. The majority of the top 10 articles pursued the convergence of blockchain technology with cloud technology or IoT. (4) Conclusions: This article illuminates the main research streams about blockchain technology in healthcare through a quantitative and qualitative review, providing implications for future research on blockchain technology.

A Blockchain-Based Secret-Data Sharing Framework for Personal Health Records in Emergency Condition

Blockchain technology is the most trusted all-in-one cryptosystem that provides a framework for securing transactions over networks due to its irreversibility and immutability characteristics. Blockchain network, as a decentralized infrastructure, has drawn the attention of various startups, administrators, and developers. This system preserves transactions from tampering and provides a tracking tool for tracing past network operations. A personal health record (PHR) system permits patients to control and share data concerning their health conditions by particular peoples. In the case of an emergency, the patient is unable to approve the emergency staff access to the PHR. Furthermore, a history record management system of the patient's PHR is required, which exhibits hugely private personal data (e.g., modification date, name of user, last health condition, etc.). In this paper, we suggest a healthcare management framework that employs blockchain technology to provide a tamper protection application by considering safe policies. These policies involve identifying extensible access control, auditing, and tamper resistance in an emergency scenario. Our experiments demonstrated that the proposed framework affords superior performance compared to the state-of-the-art healthcare systems concerning accessibility, privacy, emergency access control, and data auditing.

IoMT amid COVID-19 pandemic: Application, architecture, technology, and security

In many countries, the Internet of Medical Things (IoMT) has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates. Significant inroads have been achieved in terms of applications and technology, as well as security which have also been magnified through the rapid and widespread adoption of IoMT across the globe. A number of on-going researches show the adoption of secure IoMT applications is possible by incorporating security measures with the technology. Furthermore, the development of new IoMT technologies merge with Artificial Intelligence, Big Data and Blockchain offers more viable solutions. Hence, this paper highlights the IoMT architecture, applications, technologies, and security developments that have been made with respect to IoMT in combating COVID-19. Additionally, this paper provides useful insights into specific IoMT architecture models, emerging IoMT applications, IoMT security measurements, and technology direction that apply to many IoMT systems within the medical environment to combat COVID-19.

Intelligent interaction design research based on block chain communication technology and fuzzy system

With the increasing amount of information on the Internet, data storage management tends to be distributed. In distributed storage environment, users pay more and more attention to the timeliness of user interaction experience and the reliability of information interaction. However, the efficiency of users is often limited by the efficiency of data communication between distributed sites. One of the important goals of distributed data management is to improve the efficiency of data transmission and ensure the reliability of data transmission. Block chain technology is one of the emerging technologies supporting the development of management information system; it provides a solution for the storage, verification, transmission and communication of the distributed data. This paper focuses on solving the problem of block chain data transmission, and studies it from three aspects: improving the efficiency of data communication, ensuring the reliability of transmission, and improving the fairness of service, and different block chain data communication performance optimization strategies are proposed under the constraints of node communication capability, node trust, weight, priority of service request and other influencing factors.

Blockchain Paradigm for Healthcare: Performance Evaluation

Electronic health records (EHRs) have become a popular method to store and manage patients’ data in hospitals. Sharing these records makes the current healthcare data management system more accurate and cost-efficient. Currently, EHRs are stored using the client/server architecture by which each hospital retains the stewardship of the patients’ data. The records of a patient are scattered among different hospitals using heterogeneous database servers. These limitations constitute a burden towards a personalized healthcare, when it comes to offering a cohesive view and a shared, secure and private access to patients’ health history for multiple allied professionals and the patients. The data availability, privacy and security characteristics of the blockchain have a propitious future in the healthcare presenting solutions to the complexity, confidentiality, integrity, interoperability and privacy issues of the current client/server architecture-based EHR management system. This paper analyzes and compares the performance of the blockchain and the client/server paradigms. The results reveal that notable performance can be achieved using blockchain in a patient-centric approach. In addition, the immutable and valid patients’ data in the blockchain can aid allied health professionals in better prognosis and diagnosis support through machine learning and artificial intelligence.

The Current State of Research, Challenges, and Future Research Directions of Blockchain Technology in Patient Care: Systematic Review

Background

Blockchain offers a promising new distributed technology to address the challenges of data standardization, system interoperability, security, privacy, and accessibility of medical records.

Objective

The purpose of this review is to assess the research on the use of blockchain technology for patient care and the associated challenges and to provide a research agenda for future research.

Methods

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We queried the Cumulative Index of Nursing and Allied Health Literature (CINAHL), PubMed, Excerpta Medica dataBASE (EMBASE), and Web of Science databases for peer-reviewed research articles published up to December 2019 that examined the implementation of blockchain technology in health care settings. We identified 800 articles from which we selected 70 empirical research articles for a detailed review.

Results

Blockchain-based patient care applications include medical information systems, personal health records, mobile health and telemedicine, data preservation systems and social networks, health information exchanges and remote monitoring systems, and medical research systems. These blockchain-based health care applications may improve patient engagement and empowerment, improve health care provider access to information, and enhance the use of health care information for medical research.

Conclusions

Blockchain health information technology (HIT) provides benefits such as ensuring data privacy and security of health data, facilitating interoperability of heterogeneous HIT systems, and improving the quality of health care outcomes. However, barriers to using blockchain technology to build HIT include security and privacy vulnerabilities, user resistance, high computing power requirements and implementation costs, inefficient consensus algorithms, and challenges of integrating blockchain with existing HIT. With 51% of the research focused on medical information systems such as electronic health record and electronic medical record, and 53% of the research focused on data security and privacy issues, this review shows that HIT research is primarily focused on the use of blockchain technologies to address the current challenges HIT faces. Although Blockchain presents significant potential for disrupting health care, most ideas are in their infancy.

Investigating users’ willingness of acceptance for background music service in intelligent library

Purpose

The purpose of this paper is to study the users’ willingness for acceptance of background music service in university libraries based on intelligent campus and to improve the intelligence level of university libraries and provide a reference for the atmosphere.

Design/methodology/approach

The research method of combining theory with practice is applied, and field distribution method and network survey method are used. An algorithm model is established to investigate relevant users, and statistical analysis of the data obtained is made.

Findings

The results show that in the questionnaire survey, girls are more inclined to study in the environment of library than boys; for grade, sophomores and juniors are more inclined to go to library than other grades; through model analysis, the target users are more inclined to choose light music as background music, accounting for 65 percent. Heavy metals and other users have fewer choices, accounting for only 8 percent.

Research limitations/implications

This questionnaire is mainly filled out in paper form on site, so it only selects some nearby students as the survey objects. However, the condition of university libraries across the country must be different due to regional differences, disciplinary differences and funding differences, so the representative sample may be insufficient. Therefore, in the follow-up research, the scope of the survey should be expanded, especially the geographical scope. It should collect as much data as possible for students of different types and genders, so as to expand the applicable scope and explanatory power of the model.

Practical implications

Starting from the library scene, this research studies the acceptance intention of users of background music service in the library, which provides reference for the improvement of the intellectualization of university libraries and their atmosphere. Although different university libraries have different operation modes and service characteristics, the conclusions of this study have certain practical significance for the library industry because the library industry has many commonalities.

Originality/value

At present, the research on the background music service of University Library based on the smart campus is relatively rare and limited to the theoretical stage. Few people have deeply explored the background music service of the library, and no scholars have quantitatively studied it. In this study, based on the questionnaire and from the perspective of users, the acceptance intention of background music service users is investigated, which provides a reference for the improvement of the intellectualization of university libraries and its atmosphere. It is a research topic of great practical significance.

Blockchain in healthcare and health sciences-A scoping review

BACKGROUND

Blockchain can be described as an immutable ledger, logging data entries in a decentralized manner. This new technology has been suggested to disrupt a wide range of data-driven domains, including the health domain.

OBJECTIVE

The purpose of this study was to systematically review, assess and synthesize peer-reviewed publications utilizing/proposing to utilize blockchain to improve processes and services in healthcare, health sciences and health education.

METHOD

A structured literature search on the topic was conducted in October 2018 relevant bibliographic databases.

RESULT

39 publications fulfilled the inclusion criteria. The result indicates that Electronic Health Records and Personal Health Records are the most targeted areas using blockchain technology. Access control, interoperability, provenance and data integrity are all issues that are meant to be improved by blockchain technology in this field. Ethereum and Hyperledger fabric seem to be the most used platforms/frameworks in this domain.

CONCLUSION

This study shows that the endeavors of using blockchain technology in the health domain are increasing exponentially. There are areas within the health domain that potentially could be highly impacted by blockchain technology.

Applications of Blockchain Technology for Data-Sharing in Oncology: Results from a Systematic Literature Review

BACKGROUND

Timely sharing of electronic health records across providers, while ensuring data security and privacy, is essential for prompt care of cancer patients, as well as for the development of medical research and the enhancement of personalized medicine. Yet, it is not trivial to achieve efficient consent management, data exchange, and access-control policy enforcement, in particular, in decentralized settings, and given the gravity of the condition such as cancer. Using blockchain technology (BCT) has been recently advocated by research communities and gained momentum from the industry perspective. However, most of the proposed solutions are at the level of a prototype, and blockchain-based healthcare data management systems are not in place yet.

SUMMARY

This paper presents a systematic literature review, aiming to analyze the motivations, advantages, and limitations, as well as barriers and future challenges faced when applying the state-of-the-art distributed ledger technology in oncology. We then discuss its outcomes and propose the direction of the future research that can help to attain integration and adoption of the BCT for data-sharing, medical research, and the pharmaceutical supply chain in oncology, as well as in healthcare in general. Key Messages:BCT has the potential to enhance data-sharing (for primary care and medical research), as well as to attain optimization of the pharmaceutical supply chain by bringing properties such as transparency, traceability, and immutability to the applications. However, BCT itself cannot guarantee data privacy and security. Thus, it is never proposed as a stand-alone technology, but as a combined technology with cryptographic techniques. Regardless of the number of existing prototypes of blockchain-based healthcare systems, due to the existing barriers of the adoption (e.g., legal, social, and technological limitations), there is a lack of evaluation in real-world settings. Aiming to overcome these limitations, we propose future research directions that include design of the privacy-preserving hybrid data storage, interoperable infrastructures and architecture, and are compliant with the international laws and regulations.

Consortium Blockchain-Based Microgrid Market Transaction Research

The microgrid trading market can effectively solve the problem of in-situ consumption of distributed energy and reduce the impact of distributed generation (DG) on the grid. However, the traditional microgrid trading model has some shortcomings, such as high operation cost and poor security. Therefore, in this paper, a microgrid market trading model was developed using consortium blockchain technology and Nash game equilibrium theory. Firstly, blockchain container is used to authenticate the users who want to participate in the transaction. Then, the pricing system collects and integrates transaction requests submitted by users, then formulates transaction pricing strategy of microgrid using Nash equilibrium theory. Finally, the price, trading volume, and user information are submitted to the blockchain container for transaction matching to achieve the transaction. After the transaction is completed, its related information is recorded in the hyperledger and the dispatch system is called. The scene simulation was implemented on Fabric 1.1 platform and the results analyzed. Results show that the trading model proposed in this paper greatly reduces the cost of electricity purchase and improves the benefits of electricity sales. Besides, the model is far more capable of handling transactions than the models based on Bitcoin and Ethereum.

An Adaptive Biomedical Data Managing Scheme Based on the Blockchain Technique

A crucial role is played by personal biomedical data when it comes to maintaining proficient access to health records by patients as well as health professionals. However, it is difficult to get a unified view pertaining to health data that have been scattered across various health centers/hospital sections. To be specific, health records are distributed across many places and cannot be integrated easily. In recent years, blockchain has arisen as a promising solution that helps to achieve the sharing of individual biomedical information in a secure way, whilst also having the benefit of privacy preservation because of its immutability. This research puts forward a blockchain-based managing scheme that helps to establish interpretation improvements pertaining to electronic biomedical systems. In this scheme, two blockchains were employed to construct the base, whereby the second blockchain algorithm was used to generate a secure sequence for the hash key that was generated in first blockchain algorithm. This adaptive feature enables the algorithm to use multiple data types and also combines various biomedical images and text records. All data, including keywords, digital records, and the identity of patients, are private key encrypted with a keyword searching function so as to maintain data privacy, access control, and a protected search function. The obtained results, which show a low latency (less than 750 ms) at 400 requests/second, indicate the possibility of its use within several health care units such as hospitals and clinics.

A Review on the Role of Blockchain Technology in the Healthcare Domain

Recently, there have been increasing calls for healthcare providers to provide controls for patients over their personal health records. Nevertheless, security issues concerning how different healthcare providers exchange healthcare information have caused a flop in the deployment of such systems. The ability to exchange data securely is important so that new borderless integrated healthcare services can be provided to patients. Due to its decentralized nature, blockchain technology is a suitable driver for the much-needed shift towards integrated healthcare, providing new insights and addressing some of the main challenges of many healthcare areas. Blockchain allows healthcare providers to record and manage peer-to-peer transactions through a network without central authority. In this paper, we discuss the concept of blockchain technology and hurdles in their adoption in the healthcare domain. Furthermore, a review is conducted on the latest implementations of blockchain technology in healthcare. Finally, a new case study of a blockchain-based healthcare platform is presented addressing the drawbacks of current designs, followed by recommendations for future blockchain researchers and developers.

Blockchain Technology in Healthcare: A Comprehensive Review and Directions for Future Research

One of the most important discoveries and creative developments that is playing a vital role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter how far they are. In the last couple of years, the upsurge in blockchain technology has obliged scholars and specialists to scrutinize new ways to apply blockchain technology with a wide range of domains. The dramatic increase in blockchain technology has provided many new application opportunities, including healthcare applications. This survey provides a comprehensive review of emerging blockchain-based healthcare technologies and related applications. In this inquiry, we call attention to the open research matters in this fast-growing field, explaining them in some details. We also show the potential of blockchain technology in revolutionizing healthcare industry.

Blockchain Technology in Healthcare: A Systematic Review

Since blockchain was introduced through Bitcoin, research has been ongoing to extend its applications to non-financial use cases. Healthcare is one industry in which blockchain is expected to have significant impacts. Research in this area is relatively new but growing rapidly; so, health informatics researchers and practitioners are always struggling to keep pace with research progress in this area. This paper reports on a systematic review of the ongoing research in the application of blockchain technology in healthcare. The research methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and a systematic mapping study process, in which a well-designed search protocol is used to search four scientific databases, to identify, extract and analyze all relevant publications. The review shows that a number of studies have proposed different use cases for the application of blockchain in healthcare; however, there is a lack of adequate prototype implementations and studies to characterize the effectiveness of these proposed use cases. The review further highlights the state-of-the-art in the development of blockchain applications for healthcare, their limitations and the areas for future research. To this end, therefore, there is still the need for more research to better understand, characterize and evaluate the utility of blockchain in healthcare.

Blockchain Applications in the Biomedical Domain: A Scoping Review

Blockchain is a distributed, immutable ledger technology introduced as the enabling mechanism to support cryptocurrencies. Blockchain solutions are currently being proposed to address diverse problems in different domains. This paper presents a scoping review of the scientific literature to map the current research area of blockchain applications in the biomedical domain. The goal is to identify biomedical problems treated with blockchain technology, the level of maturity of respective approaches, types of biomedical data considered, blockchain features and functionalities exploited and blockchain technology frameworks used. The study follows the PRISMA-ScR methodology. Literature search was conducted on August 2018 and the systematic selection process identified 47 research articles for detailed study. Our findings show that the field is still in its infancy, with the majority of studies in the conceptual or architectural design phase; only one study reports real world demonstration and evaluation. Research is greatly focused on integration, integrity and access control of health records and related patient data. However, other diverse and interesting applications are emerging, addressing medical research, clinical trials, medicines supply chain, and medical insurance.