Application of AI and ML in the Indian healthcare sector - understanding and addressing the apprehensions of the stakeholders about AI implementation in Indian healthcare

Abstract

India’s population is poised to surpass China’s population in 2023. Its population has doubled since 1960 and stood at 141 Crore at the end of 2022. However, the spending on healthcare by the government barely covers the primary healthcare of all citizens. There is gross inadequacy in healthcare infrastructure, including diagnostic equipment, healthcare professionals, hospital beds, logistics, and immediate health cover. The primary healthcare sector is also in the most abysmal state in India. The application of AI and ML offers an opportunity to gap these inadequacies. AI and ML applications could also improve overall. AI could also be used to analyse the data to diagnose better and personalise treatment plans for the patients to improve efficiency. However, certain stumbling blocks exist to capitalise on the opportunity to adopt and implement the technologies. Data privacy issues must be considered, as maintaining egalitarian access to these services and developing a regulatory framework for the implementation. These barriers are further exacerbated in a country like India, where most of the population lives in rural areas with primary or no education, thus having fears and apprehension regarding technology taking over the place of the physician, who is usually revered as a god. As a result of this study, we have tried to analyse the secondary literature on implementing AI in the healthcare sector in a developing country like India and the challenges resulting from such performance. We have also tried to collect primary data through FGDs and site visits to understand the potential areas where the technology could be applied and the challenges could be alleviated.