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Unveiling the Transformative Landscape: A Bibliometric Exploration of AI Integration in Healthcare
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Author(s): Ajay Chandel (Lovely Professional University, India), Krishan Gopal (Lovely Professional University, India), Anurag Pahuja (Lovely Professional University, India)and Varun Nayyar (Chitkara University, India)
Copyright: 2024
Pages: 18
Source title:
Ethical AI and Data Management Strategies in Marketing
Source Author(s)/Editor(s): Shefali Saluja (Chitkara Business School, Chitkara University, India), Varun Nayyar (Center for Distance and Online Education, Chitkara University, India), Kuldeep Rojhe (Center for Distance and Online Education, Chitkara University, India)and Sandhir Sharma (Chitkara Business School, Chitkara University, India)
DOI: 10.4018/979-8-3693-6660-8.ch014
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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.
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