Authors : Srinivas Lanka; Pavithra Madala

Volume/Issue : Volume 9 - 2024, Issue 10 - October

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Google Scholar : https://tinyurl.com/7w7yskna

Scribd : https://tinyurl.com/yxyy79bt

DOI : https://doi.org/10.38124/ijisrt/IJISRT24OCT089

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : Artificial intelligence (AI) has the potential to revolutionize healthcare by enhancing diagnostic accuracy, reducing administrative burdens, and providing personalized treatment. However, the slow adoption of AI in healthcare is due to obstacles associated with ethical considerations, data management, regulations, and technological capabilities. The results of our study highlight specific challenges related to ethics, technology, regulatory, social, economic, and workforce barriers that affect the implementation of AI in healthcare. We aim to improve current knowledge by providing a more comprehensive understanding, by bridging the gap, and addressing the barriers to implement AI in the healthcare sector.

Keywords : Artificial Intelligence, Implementation Gap, Machine Learning, Barriers.

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