Affiliation:
1. Lovely Professional University, India
2. Chitkara University, India
Abstract
This study uses bibliometric analysis to investigate the methods, thematic insights, and revolutionary possibilities of AI integration in healthcare. It provides insights into the evolution of AI in healthcare through topic mapping, keyword co-occurrence, co-citation, and bibliographic coupling. Keyword co-occurrence highlights important themes like federated learning, digital healthcare, and the internet of things, while co-citation analysis identifies emerging subjects like federated machine learning. The relationships between different research streams and the effects of explainable AI and machine learning on healthcare IT are made clear by the bibliographic coupling. Thematic mapping offers a graphic synopsis of several subjects, from systemic modifications to technical innovations. By educating stakeholders, this study helps them make decisions and sets the stage for future research. It directs efforts to maximize AI's potential for bettering patient outcomes and providing healthcare to practitioners, policymakers, and researchers.