The healthcare sector in India has experienced significant transformations owing to the advancement in technology and infrastructure. Despite these transformations, there are major challenges to address critical issues like insufficient healthcare infrastructure for the country’s huge population, limited accessibility, shortage of skilled professionals, and high-quality care. Artificial intelligence (AI)-driven solutions have the potential to lessen the stress on India’s healthcare system; however, integrating trustworthy AI in the sector remains challenging due to ethical and regulatory constraints. This study aims to critically review the current status of the development of AI systems in Indian healthcare and how well it satisfies the ethical and legal aspects of AI, as well as to identify the challenges and opportunities in adoption of trustworthy AI in the Indian healthcare sector. This study reviewed 15 articles selected from a total of 1136 articles gathered from two electronic databases, PubMed and Google Scholar, as well as project websites. This study makes use of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). It finds that the existing studies mostly used conventional machine learning (ML) algorithms and artificial neural networks (ANNs) for a variety of tasks, such as drug discovery, disease surveillance systems, early disease detection and diagnostic accuracy, and management of healthcare resources in India. This study identifies a gap in the adoption of trustworthy AI in Indian healthcare and various challenges associated with it. It explores opportunities for developing trustworthy AI in Indian healthcare settings, prioritizing patient safety, data privacy, and compliance with ethical and legal standards.

Server-less computing is a novel cloud-based paradigm that is gaining popularity today for running widely distributed applications. When it comes to server-less computing, features are available via subscription. Server-less computing is advantageous to developers since it lets them install and run programs without worrying about the underlying architecture. A common choice for code deployment these days, server-less design is preferred because of its independence, affordability, and simplicity. The healthcare industry is one excellent setting in which server-less computing can shine. In the existing literature, we can see that fewer studies have been put forward or explored in the area of server-less computing with respect to smart healthcare systems. A cloud infrastructure can help deliver services to both users and healthcare providers. The main aim of our research is to cover various topics on the implementation of server-less computing in the current healthcare sector. We have carried out our studies, which are adopted in the healthcare domain and reported on an in-depth analysis in this article. We have listed various issues and challenges, and various recommendations to adopt server-less computing in the healthcare sector.