• Dipanjan Dutta
• Anusudha.K

Artificial intelligence (AI) in healthcare is reviewed methodically in this work, emphasizing the technology's problems and potential uses. AI technologies, such as natural language processing (NLP), predictive analytics, clinical decision support, drug discovery, robot-assisted surgery, public health, machine learning, and risk identification, are revolutionizing healthcare by aiding in diagnosis, tailoring treatments, monitoring patients, streamlining operations, and enhancing public health outcomes. Notwithstanding the potential benefits, several significant barriers must be overcome before AI can be fully integrated into healthcare. These difficulties include worries about privacy and data security, moral and legal quandaries, problems with integration and interoperability, difficulties with scale and accessibility, and the difficulties of interacting with AI in human-human relationships. This review emphasizes the importance of robust cybersecurity measures, ethical standards, clear legal frameworks, and universal interoperability standards, along with equitable access to AI technologies. It also proposes that improving healthcare professional education, boosting research and development, and fostering interdisciplinary collaboration are critical for overcoming these difficulties and fully achieving AI's promise in healthcare.

AI, diagnostics, clinical decision support, drug discovery, NLP, robot assisted surgery, public health, and risk identification.

"Revolutionizing Healthcare: The Impact of Artificial Intelligence on Patient Care Literature Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 9, page no.c395-c401, September-2024, Available :http://www.jetir.org/papers/JETIR2409246.pdf

"Revolutionizing Healthcare: The Impact of Artificial Intelligence on Patient Care Literature Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 9, page no. ppc395-c401, September-2024, Available at : http://www.jetir.org/papers/JETIR2409246.pdf