Implication of Big Data Analytics, Artificial Intelligence, Machine Learning and Deep Learning in public health sector of Bangladesh: A scoping review (Preprint)

Abstract

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 global public health, including Bangladesh. The increased adoption of these technologies in healthcare delivery within Bangladesh has sparked their integration into public health research, resulting in a noticeable surge in related studies. However, a critical gap exists, as there is a lack of comprehensive evidence regarding the research landscape, regulatory challenges, use-cases, and the application and adoption of BDA, AI, ML, and DL in the Bangladeshi public health sector. This gap impedes the attainment of optimal results. As a leading implementer of digital technologies, bridging this gap is urgent for the effective utilization of these advancing technologies in Bangladesh. OBJECTIVE The authors conducted this scoping review with the intention of collating (a) the existing research in Bangladesh’s public health sector using the technologies above and synthesizing their findings; (b) the limitations faced by researchers in integrating the mentioned technologies into public health research. METHODS Medline (through Pubmed), IEEE Explorer, Scopus, and Embase databases were searched to identify published research articles in between 1st January, 2000 to 10th September, 2023 meeting the following inclusion criteria: (a) any study using any of the BDA, AI, ML, and DL technologies and using public health datasets for predicting health issues and forecasting any kind of outbreak; (b) studies primarily focusing on Bangladesh public health issues; (c) original research articles published in peer-reviewed journals and conference proceedings written in English. RESULTS With the initial search, we identified 1,653 studies. Following the inclusion and exclusion criteria and a full-text review, 77 articles were finally included in this review. There has been a significant increase in studies over the last five years (2017–2023). Among the 77 studies, the majority utilized ML models (n = 65, 84.4%). A smaller proportion of studies incorporated AI (n = 4, 5.2%), DL (n = 7, 9.1%), and BDA (n = 1, 1.3%) technologies. Among the reviewed articles, 52% (n = 40) relied on primary data, while the remaining 48% (n = 37) utilized secondary data. The primary research areas of focus were infectious diseases (n = 15, 19.5%), non-communicable diseases (n = 23, 29.9%), child health (n = 11, 14.3%), and mental health (n = 9, 11.7%). CONCLUSIONS This scoping review highlights remarkable progress in leveraging BDA, AI, ML, and DL within Bangladesh's public health sector. The observed surge in studies over the last five years underscores the increasing significance of AI and related technologies in public health research. Notably, the majority of studies focused on ML models, unveiling opportunities for advancements in predictive modeling. This overview encapsulates the current state of technological integration and propels us into a promising era for the future of digital Bangladesh.