Role of artificial intelligence in health sector: review of literature

Authors

  • Kamlesh Sharma Department of Community Medicine, Dr. Y.S. Parmar Government Medical College Nahan, Himachal Pradesh, India
  • Ram Lal Sharma Department of Ophthalmology, Indira Gandhi Medical College Shimla, Himachal Pradesh, India

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20261451

Keywords:

Artificial intelligence, Machine learning, Personalised medicine, Benefits, Ethical issues, Challenges, Health sector

Abstract

Artificial Intelligence will play a significant role in various health sectors in near future.  AI technologies like machine learning, deep learning, natural language processing and robotics help to analyse large and complex datasets. This analysis leads to early disease detection, personalised treatment and predictive risk assessment. AI supports public health efforts by predicting outbreak, monitoring health parameters and allocating resources. Despite its benefits and challenges, integrating AI into healthcare system remains crucial. This paper explores Evolution of AI in healthcare, the technologies involved, its benefits, challenges and ethical considerations and future prospects.

References

Ahadi S, Carroll A. Developing an aging clock using deep learning on retinal images. Google Research Blog. 2023.

Mullainathan S, Obermeyer Z. Solving medicine's data bottleneck: Nightingale Open Science. Nature Medicine. 2022;28(5):897-9. DOI: https://doi.org/10.1038/s41591-022-01804-4

Jimma BL. Artificial intelligence in healthcare: A bibliometric analysis. Telemat Inform Rep. 2023;9(1):100041. DOI: https://doi.org/10.1016/j.teler.2023.100041

Sharma AK, Sharma R. Bibliometric exploration of artificial intelligence applications in healthcare: trends and future directions. J Public Health Dev. 2026;23(2):281-303. DOI: https://doi.org/10.55131/jphd/2025/230220

Shortliffe EH, Sepulveda MJ. Clinical decision support in the era of artificial intelligence. JAMA. 2018;320(21):2199-200. DOI: https://doi.org/10.1001/jama.2018.17163

Jiang F, JiangY, Zhi H, Dong Yi, li H, Ma S, et al. Artificial Intelligence in health care: past, present and future. Stroke Vasc Neural. 2017;2(4):230-43. DOI: https://doi.org/10.1136/svn-2017-000101

Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, et al. Dermatologist classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115-8. DOI: https://doi.org/10.1038/nature21056

Rajkomar A, Dean J, Kohane I. Machine learning in Medicine. N England J Med. 2019;380(14):1347-58. DOI: https://doi.org/10.1056/NEJMra1814259

WHO. Ethics and Governance of Artificial Intelligence for health. 2021. Available at: https://www.who.int/publications/i/item/9789240029200. Accessed on 22 February 2026.

Turcian D, Stoicu-Tivadar V. Artificial intelligence in primary care: An Overview. Stud Health Technol Inform. 2022;289:208-11. DOI: https://doi.org/10.3233/SHTI210896

Xie Y, Lu L, Gao F, He SJ, Zhao HJ, Fang Y, et al. Integration of artificial intelligenceblockchain and wearable technology for chronic disease management: A new paradigm in smart healthcare. Curr Med Sci. 2021;41(6):1123-33. DOI: https://doi.org/10.1007/s11596-021-2485-0

Guo J, Li B. The Application of Medical Artificial IntelligenceTechnology in Rural Areas of Developing Countries. Health Equity. 2018;2(1):174-81. DOI: https://doi.org/10.1089/heq.2018.0037

Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-8. DOI: https://doi.org/10.7861/futurehosp.6-2-94

Floridi L, Luetge C, Pagallo U, Schafer B, Valcke P, Vayena E, et al. Key Ethical Challenges in the European Medical Information Framework. Minds Mach. 2019;29(3):355-71. DOI: https://doi.org/10.1007/s11023-018-9467-4

Russell SJ, Norvig P. Artificial Intelligence: A Modern Approach. 3rd ed: Prentice Hall. 2010.

Shortliffe EH. MYCIN: A knowledge-based computer program applied to infectious diseases. Proc Annu Symp Compute Apple Med Care. 1977;66-9.

Shortliffe EH, Cimino JJ. Biomedical informatics: Computer Applications in HealthCare and Biomedicine. 4th ed. London: Springer. 2014. DOI: https://doi.org/10.1007/978-1-4471-4474-8

Ferrucci D, Brown E, Chu- Carroll J, Fan J, Gondek D, Kalyanpur AA, et al. Building Watson: An overview of the DeepQA project. AI Mag. 2010;31(3):59-79. DOI: https://doi.org/10.1609/aimag.v31i3.2303

Abràmoff MD, Lavin PT, Birch M, Shah N, Folk JC. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ Digit Med. 2018;1:39. DOI: https://doi.org/10.1038/s41746-018-0040-6

Dave T, Athaluri SA, Singh S. ChatGPT in medicine: An overview of it applications, advantages, limitations, future prospects and ethical considerations. Front Artif Intell. 2023;1-5. DOI: https://doi.org/10.3389/frai.2023.1169595

Liu J, Wang C, Liu S. Utility of ChatGPT in clinical practice. J Med Internet Res. 2023;25:e48568. DOI: https://doi.org/10.2196/48568

Le Cun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521(7553):436-44. DOI: https://doi.org/10.1038/nature14539

Jurafsky D, Martin JH. Speech and Language processing. 3rd ed. Pearson. 2023.

Riek LD. Healthcare robotics. Commun ACM. 2017;60(11):68-78. DOI: https://doi.org/10.1145/3127874

Kumawat J, Tanwani L. Predictive Analytics and Data mining: Concepts and Applications. New Delhi: Wiley. 2020.

Cheng JZ, Ni D, Qin J, Chou YH, Tiu CM, ChangY-C, et al. Computer-aided diagnosis with deep learning architecture: applications to breast lesions in US images and pulmonary nodulesin CT scans. Sci Rep. 2016;6:24454. DOI: https://doi.org/10.1038/srep24454

Goodfellow I, Bengio Y, Courville A. Deep Learning. Cambridge (MA): MIT Press. 2016.

Rajkomar A, Oren E, Chen K, Dai AM, Hajaj N, Hardt M, et al. Scalable and accurate deep learning with electronic health records. NPJ Digit Med. 2018;1:18. DOI: https://doi.org/10.1038/s41746-018-0029-1

Shimabukuro DW, Barton CW, Feldman MD, Mataraso SJ, Das R. Effect of a learning- based severe sepsis prediction algorithm on patient survival and hospital length of stay: A randomised clinical trial. BMJ Open Respir Res. 2017;4:e000234. DOI: https://doi.org/10.1136/bmjresp-2017-000234

Kuwaiti AA, Nazer K, Reedy AA, Shehri SA, Muhana AA, Subbarayalu AV, et al. A Review of the Role of Artificial Intelligence in Health Care. J Press Med. 2023;13(6):951. DOI: https://doi.org/10.3390/jpm13060951

Shaik T, Tao X, Higgins N, Li L, Gurujan Raj, Zhou X, et al. Remote Patient Monitoring using AI. arXiv preprint. 2023;13(2). DOI: https://doi.org/10.1002/widm.1485

Rumbold JMM, Pierscionek B. The effect of the General Data Protection on medical research. J Med Internet Res. 2017;19(2):e47. DOI: https://doi.org/10.2196/jmir.7108

Ramos PIP, Marcilio I, Bento AI, Penna GO, Oliveira JF de, Khouri R, et al. Combining digital and molecular approaches using health and alternate data sources in a next-generation surveillance system for anticipating outbreaks of pandemic potential. JMIR Public Health Surveill. 2024;10:e47673. DOI: https://doi.org/10.2196/47673

Topol EJ. High performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56. DOI: https://doi.org/10.1038/s41591-018-0300-7

Bastami AM, Moin S, Ahmad S, Ahmed AR, Pouwels S, Hajibandeh S. Narrative Review: Artificial Intelligence in healthcare: applications, challenges and future directions. Frontiers. 2025;7:1644041.

Sarkar A. The Impact and Potential of Artificial Intelligence in Healthcare. Critical Review of Current Applications and Future Directions. IJRASET. 2023;11(8):2089-91. DOI: https://doi.org/10.22214/ijraset.2023.55537

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Published

2026-04-30

How to Cite

Sharma, K., & Sharma, R. L. (2026). Role of artificial intelligence in health sector: review of literature . International Journal Of Community Medicine And Public Health, 13(5), 2569–2573. https://doi.org/10.18203/2394-6040.ijcmph20261451

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Section

Review Articles