Implications of Big Data Analytics, AI, Machine Learning, and Deep Learning in the Health Care System of Bangladesh: Scoping Review

Background: The rapid advancement of digital technologies, particularly in big data analytics (BDA), artificial intelligence(AI), machine learning (ML), and deep learning (DL), is reshaping the global health care system, including in Bangladesh. Theincreased adoption of these technologies in health care delivery within Bangladesh has sparked their integration into health careand public health research, resulting in a noticeable surge in related studies. However, a critical gap exists, as there is a lack ofcomprehensive evidence regarding the research landscape; regulatory challenges; use cases; and the application and adoption ofBDA, AI, ML, and DL in the health care system of Bangladesh. This gap impedes the attainment of optimal results. As Bangladeshis a leading implementer of digital technologies, bridging this gap is urgent for the effective use of these advancing technologies.Objective: This scoping review aims to collate (1) the existing research in Bangladesh's health care system, using theaforementioned technologies and synthesizing their findings, and (2) the limitations faced by researchers in integrating theaforementioned technologies into health care research.Methods: MEDLINE (via PubMed), IEEE Xplore, Scopus, and Embase databases were searched to identify published researcharticles between January 1, 2000, and September 10, 2023, meeting the following inclusion criteria: (1) any study using any ofthe BDA, AI, ML, and DL technologies and health care and public health datasets for predicting health issues and forecastingany kind of outbreak; (2) studies primarily focusing on health care and public health issues in Bangladesh; and (3) original researcharticles published in peer-reviewed journals and conference proceedings written in English.Results: With the initial search, we identified 1653 studies. Following the inclusion and exclusion criteria and full-text review,4.66% (77/1653) of the articles were finally included in this review. There was a substantial increase in studies over the last 5years (2017-2023). Among the 77 studies, the majority (n=65, 84%) used ML models. A smaller proportion of studies incorporatedAI (4/77, 5%), DL (7/77, 9%), and BDA (1/77, 1%) technologies. Among the reviewed articles, 52% (40/77) relied on primary data, while the remaining 48% (37/77) used secondary data. The primary research areas of focus were infectious diseases (15/77,19%), noncommunicable diseases (23/77, 30%), child health (11/77, 14%), and mental health (9/77, 12%).Conclusions: This scoping review highlights remarkable progress in leveraging BDA, AI, ML, and DL within Bangladesh'shealth care system. The observed surge in studies over the last 5 years underscores the increasing significance of AI and relatedtechnologies in health care research. Notably, most (65/77, 84%) studies focused on ML models, unveiling opportunities foradvancements in predictive modeling. This review encapsulates the current state of technological integration and propels us intoa promising era for the future of digital Bangladesh.