An analysis of application of health informatics in Traditional Medicine: A review of four Traditional Medicine Systems

Overview and limitations of database in global traditional medicines: A narrative review

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

An exploratory study on becoming a traditional spiritual healer among Baganda in Central Uganda

Traditional medicinal knowledge and healing practices of indigenous spiritual healers play important roles in health care, and contribute towards achieving Universal Health Care. Traditional spiritual healers (TSHs) are grouped into three categories. One category of Baganda TSHs, Balubaale, engage ancestral spirits during health management. Balubaale are socially significant but not legally accepted. Their initiation and training practices have not been documented in Uganda. The study purpose was to understand and establish the training of traditional spiritual healers. Twelve (10M, 2F); practicing TSHs in Central Uganda were purposively selected and recruited between 15th July 2019 and 29th April 2020, and were prospectively interacted with for 24 months. Transcribed data was coded and thematically analyzed using ATLAS ti. 22 computer software and presented based on an inductive approach. Findings show key areas of TSHs training include connecting with ancestral spirits and the spiritual powers of non-materials and materials such as living and non-living things through rituals. Spiritual healers train in diagnosis and health management based on ancestral spirits and they finally pass out in a communal ceremony witnessed by family and community members. We conclude that TSHs undergo training and are supervised and supported by experienced spiritualists, family and the community. We recommend similar studies among other ethnic groups to contextualize the process of becoming a TSH, compare and harmonize findings to facilitate inter-medical systems communication and policy considerations.

Attitudes and perceptions of traditional health practitioners towards documentation of patient health information in their practice in eThekwini Municipality, KwaZulu-Natal, Natal Province, South Africa

BACKGROUND

Documentation of patient health information in the form of patient medical records (PMRs) is an essential, ethical and regulatory requirement in any healthcare system. African traditional medicine (ATM) exists parallel to biomedicine and continues to play a significant role in primary healthcare of the majority of South Africans. The World Health Organization (WHO) has promoted the integration of ATM into the national health system of South Africa. Patient health information documentation can facilitate this integration, and PMRs promote communication between the two health systems through referrals. Documentation in biomedicine is a clear, compulsory, routine activity, but does not occur regularly or routinely in ATM.

OBJECTIVE

To examine the attitudes and perceptions of traditional health practitioners (THPs) towards documentation of patient health information in their practice.

METHODS

This quantitative cross-sectional survey involved snowball sampling to recruit THPs in Umlazi Township and rural parts surrounding the township, in Durban, South Africa. A semi-structured questionnaire was used. Quantitative data were analysed using SPSS 25 and the Relative Importance Index (RII) and qualitative data were analysed using Excel for themes.

RESULTS

Sampling resulted in 248 THPs of whom 178 (72%) were females. The RII ranked the factors that negatively influenced the participants' attitudes towards documentation of patient health information. Of the 178 females who participated in the study, 129 (72.5%) showed their willingness to introduce documentation in their practice. Of the 127 participants with less than 10 years of practice experience, 126 (99.2%) agreed to the importance of introducing PMRs in their practice. The majority of participants perceived documentation of patient health information as vital to improve their practice. A prominent theme was that the THPs regarded documenting patient health information as important and effective in their practice.

CONCLUSION

More than half of participants showed positive attitudes and perceptions towards documenting of patient health information in ATM. The majority of the participants in this study acknowledged the importance of introducing documentation of patient health information in their practice even though they lacked experience and more knowledge. This reflects a need for essential intervention in developing specialised tools to begin promoting documentation of patient health information in ATM.

Translational Informatics for Natural Products as Antidepressant Agents

Depression, a neurological disorder, is a universally common and debilitating illness where social and economic issues could also become one of its etiologic factors. From a global perspective, it is the fourth leading cause of long-term disability in human beings. For centuries, natural products have proven their true potential to combat various diseases and disorders, including depression and its associated ailments. Translational informatics applies informatics models at molecular, imaging, individual, and population levels to promote the translation of basic research to clinical applications. The present review summarizes natural-antidepressant-based translational informatics studies and addresses challenges and opportunities for future research in the field.

Different Data Mining Approaches Based Medical Text Data

The amount of medical text data is increasing dramatically. Medical text data record the progress of medicine and imply a large amount of medical knowledge. As a natural language, they are characterized by semistructured, high-dimensional, high data volume semantics and cannot participate in arithmetic operations. Therefore, how to extract useful knowledge or information from the total available data is very important task. Using various techniques of data mining can extract valuable knowledge or information from data. In the current study, we reviewed different approaches to apply for medical text data mining. The advantages and shortcomings for each technique compared to different processes of medical text data were analyzed. We also explored the applications of algorithms for providing insights to the users and enabling them to use the resources for the specific challenges in medical text data. Further, the main challenges in medical text data mining were discussed. Findings of this paper are benefit for helping the researchers to choose the reasonable techniques for mining medical text data and presenting the main challenges to them in medical text data mining.

Improvements in HOMA indices and pancreatic endocrinal tissues in type 2-diabetic rats by DPP-4 inhibition and antioxidant potential of an ethanol fruit extract of Withania coagulans

CONTEXT

Withania coagulans (Stocks) Dunal fruits are used in the therapeutics of several ailments due to possessing of potent phytoconstituents which is also used traditionally for curing the diabetes.

OBJECTIVE

The present study was assessing the amelioration potential of the phytochemicals of an ethanol fruit extract of W. coagulans (Stocks) Dunal in the HOMA (Homeostatic model assessment) indices and pancreatic endocrinal tissues by inhibition of DPP-4 and antioxidants activities.

MATERIAL AND METHODS

The identification of phytoconstituents of the test extract was performed by LCMS. Further, assessments of in-vitro, in-vivo and in-silico were achieved by following standard methods. In-vivo studies were conducted on type-2 diabetic rats.

RESULTS

The chosen extract inhibited DPP-4 activity by 63.2% in an in vitro assay as well as significantly inhibit serum DPP-4 levels. Accordingly, the administration of the ethanol fruit extract resulted in a significant (P ≤ 0.001) alterations in the lipid profile, antioxidant levels, and HOMA indices. Moreover, pancreatic endocrinal tissues (islet of Langerhans) appeared to have the restoration of normal histoarchitecture as evidenced by increased cellular mass. Molecular docking (Protein-ligands) of identified phytoconstituents with DPP-4 (target enzyme) shown incredibly low binding energy (Kcal/mol) as required for ideal interactions. ADMET analysis of the pharmacokinetics of the identified phytoconstituents indicated an ideal profile as per Lipinski laws.

CONCLUSION

It can be concluded that the phytoconstituents of an ethanol fruit extract of W. coagulans have the potential to inhibit DPP-4 which result in improved glucose homeostasis and restoration of pancreatic endocrinal tissues in type-2 diabetic rats.

Comparing Smartphone Apps for Traditional Chinese Medicine and Modern Medicine in China: Systematic Search and Content Analysis

Background

Traditional Chinese medicine (TCM) is an integral part of mainstream medicine in China, with theories and practices that are completely different from modern medicine. TCM should not be ignored or confused with modern medicine in the analysis of the Chinese health care system, including the analysis of mobile health (mHealth) apps. To date, differences between TCM apps and modern medicine apps have not be systematically investigated.

Objective

The aim of this study was to systematically compare the quality of apps for TCM and modern medicine in China.

Methods

In December 2020, we searched iOS (iTunes) and Android (Tencent, Oppo, and Huawei app stores) platforms for all mHealth apps and then categorized them as TCM or modern medicine apps if they were included in the final analysis. The included apps were downloaded on smartphones and assessed by 2 reviewers on the following 4 aspects: (1) data in the app stores, including user ratings, download counts, cost, target users, and year of last update; (2) functionality; (3) quality of the app content as determined by the Mobile App Rating Scale (MARS); and (4) analysis of the app privacy and security.

Results

In total, 658 apps were analyzed, including 261 TCM medicine apps and 397 modern medicine apps. The average download count of modern medicine apps (approximately 5 million) was more than 10 times that of TCM apps (approximately 400,000). Regarding functionalities, 64.7% (257/397) of modern medicine apps provided telemedicine (74/261, 28.4% in TCM apps), 62.7% (249/397) provided registration (70/261, 26.8% in TCM apps), and 45.6% (181/397) provided communication (38/261, 14.6% in TCM apps). A larger proportion of TCM apps provided prescription and medication management (144/261, 55.2% in TCM apps versus 168/397, 42.3% in modern medicine apps). The majority of modern medicine apps (329/397, 82.9%) combined ≥3 functionalities compared with one-third of TCM apps (93/261, 34.6%). We then selected 81 top apps for quality and safety assessment (41 TCM apps and 40 modern medicine apps). Of these, the mean overall MARS score of TCM apps (2.7, SD 0.5) was significantly lower than modern medicine apps (3.6, SD 0.4). Almost all modern medicine apps (38/40, 95%) addressed privacy and security by providing a privacy policy and describing how to protect personal data, but less than half of the TCM apps (18/41, 44%) described this information (P<.001).

Conclusions

The different functionalities reflect the distinct innate characteristics of these two medical systems. Although great progress has been made and the Chinese mHealth market size is large, there still exist many opportunities for future development, especially for TCM.

Comparison Among Garlic, Berberine, Resveratrol,Hibiscus sabdariffa, GenusZizyphus, Hesperidin, Red Beetroot,Catha edulis,Portulaca oleracea, and Mulberry Leaves in the Treatment of Hypertension and Type 2 DM: A Comprehensive Review

Diabetes mellitus (DM) and hypertension are 2 of the most prevalent diseases with poor impact on health status worldwide. In most cases, they coexist with other metabolic disorders as well as cardiac, micro- and macrovascular complications. Many plants are known for their hypotensive, cardioprotective, and/or antidiabetic activities. Their active ingredients either identified and isolated or still utilized as herbal preparations of certain plant parts. The use of medicinal plants comprises the main basis for most of the traditional medicine (TM) systems and procedures. As conventional medicines seem insufficient to control such progressive diseases, herbal agents from TM could be used as adjuvant with good impact on disease control and progression as well as other concomitant health conditions. The aim of this study is to compare the efficacy of 10 different herbal medicines of botanical origin or herbal preparations in the management of hypertension and its cardiovascular complications and type 2 DM along with various coexisting health disorders. These herbal medicines are garlic, berberine, resveratrol, Hibiscus sabdariffa, Zizyphus ( oxyphylla, mucronate, jujube, rugosa), hesperidin, red beetroot, Catha edulis, mulberry leaves, and Portulaca oleracea.

The necessity to develop a national classification system for Iranian traditional medicine

BACKGROUND

Classification of disease and interventions in traditional medicine (TM) is necessary for standardised coding of information. Currently, in Iran, there is no standard electronic classification system for disease and interventions in TM.

OBJECTIVE

The current study aimed to develop a national framework for the classification of disease and intervention in Persian medicine based on expert opinion.

METHOD

A descriptive cross-sectional study was carried out in 2018. The existing systems for the classification of disease and interventions in TM were reviewed in detail, and some of the structural and content characteristics were extracted for the development of the classification of Iranian traditional medicine. Based on these features, a self-administered questionnaire was developed. Study participants (25) were experts in the field of Persian medicine and health information management in Tehran medical universities.

RESULTS

Main axes for the classification of disease and interventions were determined. The most important applications of the classification system were related to clinical coding, policymaking, reporting of mortality and morbidity data, cost analysis and determining the quality indicators. Half of the participants (50%) stated that the classification system should be designed by maintaining the main axis of the World Health Organization classification system and changing the subgroups if necessary. A computer-assisted coding system for TM was proposed for the current study.

CONCLUSION

Development of this classification system will provide nationally comparable data that can be widely used by governments, national organisations and academic researchers.

A systematic literature review and classification of knowledge discovery in traditional medicine

INTRODUCTION AND OBJECTIVE

Despite the importance of machine learning methods application in traditional medicine there is a no systematic literature review and a classification for this field. This is the first comprehensive literature review of the application of data mining methods in traditional medicine.

METHOD

We reviewed 5 database between 2000 to 2017 based on the Kitchenham systematic review methodology. 502 articles were identified and reviewed for their relevance to application of machine learning methods in traditional medicine, 42 selected papers were classified and categorized on four dimension; 1) application domain of data mining techniques in traditional medicine; 2) the data mining methods most frequently used in traditional medicine; 3) main strength and limitation of data mining techniques in traditional medicine; 4) the performance evaluation methods in data mining methods in traditional medicine.

RESULT

The result obtained showed that main application domain of data mining techniques in traditional medicine was related to syndrome differentiation. Bayesian Networks (BNs), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) were recognized as being the methods most frequently applied in traditional medicine. Furthermore, each data mining techniques has its own strength and limitations when applied in traditional medicine. Single scaler methods were frequently used for performance evaluation of data mining methods.

CONCLUSION

Machine learning methods have become an important research field in traditional medicine. Our research provides information about this methods by examining the related articles.

The Role of Artificial Intelligence in Clinical Decision Support Systems and a Classification Framework

Clinical decision support systems are meant to improve the quality of decision-making in healthcare. Artificial intelligence is the science of creating intelligent systems that solve complex problems at the level of or better than human experts. Combining artificial intelligence methods into clinical decision support will enable the utilization of large quantities of data to produce relevant decision-making information to practitioners. This article examines various artificial intelligence methodologies and shows how they may be incorporated into clinical decision-making systems. A framework for describing artificial intelligence applications in clinical decision support systems is presented.

New approach to generating insights for aging research based on literature mining and knowledge integration

The proportion of the elderly population in most countries worldwide is increasing dramatically. Therefore, social interest in the fields of health, longevity, and anti-aging has been increasing as well. However, the basic research results obtained from a reductionist approach in biology and a bioinformatic approach in genome science have limited usefulness for generating insights on future health, longevity, and anti-aging-related research on a case by case basis. We propose a new approach that uses our literature mining technique and bioinformatics, which lead to a better perspective on research trends by providing an expanded knowledge base to work from. We demonstrate that our approach provides useful information that deepens insights on future trends which differs from data obtained conventionally, and this methodology is already paving the way for a new field in aging-related research based on literature mining. One compelling example of this is how our new approach can be a useful tool in drug repositioning.

Alisol A 24-Acetate and Alisol B 23-Acetate Induced Autophagy Mediates Apoptosis and Nephrotoxicity in Human Renal Proximal Tubular Cells

Two natural compounds alisol A 24-acetate (24A) and alisol B 23-acetate (23B) are abundant in Rhizoma alismatis. In the present study, we evaluated the induction of 24A and 23B on apoptosis and possible nephrotoxicity of human renal proximal tubular (HK-2) cells by activating autophagy and also explored its regulation on PI3K/Akt/mTOR signaling pathway. Presently, Clusterin, Kim-1, and TFF-3 were considered to be new bioindicators of nephrotoxicity. Interestingly, the protein expression and mRNA levels of Clusterin, Kim-1 and TFF-3 could be significantly increased by 23B and 24A in vivo and in vitro. Furthermore, cell apoptosis could be triggered by 23B and 24A via significantly decreasing the protein expression and mRNA levels of Bcl-2 and Bcl-xl. Autophagy of HK-2 cells could be induced by both 23B and 24A via significantly enhancing the ratio of LC3II/LC3I, the protein expression of Beclin-1 as well as the mRNA levels of LC3 and Beclin-1. Meanwhile, PI3K/Akt/mTOR signaling pathway could be inhibited by these two compounds. An autophagy inhibitor, 3-methyladenine, could partially reverse cell viability and conversely change the ratio of LC3II/LC3I and the protein expression of Bcl-2 and Kim-1. Thus this study helped to understand that 23B and 24A induced autophagy resulted in apoptosis and nephrotoxicity through inhibiting PI3K/Akt/mTOR signaling pathway, facilitating further studies for nephrotoxicity induced by these two compounds and could be beneficial for safe use of Rhizoma alismatis in clinic.