Author(s): Purohit Saraswati, Suneel Kumar C. N.

Email(s): saruswati28@gmail.com

DOI: 10.52711/jnmr.2024.26   

Address: Purohit Saraswati, Suneel Kumar C. N.
1Assistant Professor, HOD Department of Psychiatric Nursing, Karnataka, India.
2Assistant Lecturer JSS College of Nursing, Mysuru, Karnataka, India.
*Corresponding Author

Published In:   Volume - 3,      Issue - 3,     Year - 2024


ABSTRACT:
Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy, personalizing treatment plans, streamlining administrative tasks, and advancing research capabilities. This abstract explores the multifaceted applications of AI in healthcare, highlighting its potential to revolutionize the industry. AI technologies, including machine learning, natural language processing, and computer vision, are being integrated into various aspects of healthcare. In diagnostics, AI algorithms can analyze medical images, identify patterns, and detect anomalies with precision often surpassing human capabilities. For instance, AI systems have demonstrated proficiency in detecting cancers, retinal diseases, and cardiovascular conditions from medical imaging and data.1


Cite this article:
Purohit Saraswati, Suneel Kumar C. N.. AI in Health Care: A Comprehensive Review. A and V Pub Journal of Nursing and Medical Research. 2024; 3(3):112-4. doi: 10.52711/jnmr.2024.26

Cite(Electronic):
Purohit Saraswati, Suneel Kumar C. N.. AI in Health Care: A Comprehensive Review. A and V Pub Journal of Nursing and Medical Research. 2024; 3(3):112-4. doi: 10.52711/jnmr.2024.26   Available on: https://jnmronline.com/AbstractView.aspx?PID=2024-3-3-9


REFERENCES:
1.    Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017; 542(7639): 115-118.
2.    Obermeyer Z, Emanuel EJ. Predicting the Future — Big Data, Machine Learning, and Clinical Medicine. N Engl J Med. 2016; 375(13): 1216-1219.
3.    Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25(1): 44-56.
4.    Rajkomar A, Dean J, Kohane I. Machine Learning in Medicine. N Engl J Med. 2019; 380(14): 1347-1358.
5.    Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017; 2(4): 230-243.

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