Author(s):
Nikhil M. Patil, Prashant R. Wagh, Anand G. Gavale, Chetan J. Girase
Email(s):
nikhilpatil5501@gmail.com
DOI:
10.52711/2231-5659.2026.00006
Address:
Nikhil M. Patil, Prashant R. Wagh, Anand G. Gavale, Chetan J. Girase
Assistant Professor, SVS’s Dadasaheb Rawal Pharmacy College, Dondaicha-Dhule,
Affiliated To: Dr. Babasaheb Ambedkar Technological University, Lonere-Raigad, India.
*Corresponding Author
Published In:
Volume - 16,
Issue - 1,
Year - 2026
ABSTRACT:
Artificial Intelligence (AI) is rapidly transforming modern healthcare, evolving from experimental tools to validated, clinical-grade systems with the potential to enhance diagnostic accuracy, optimize treatment, and improve patient outcomes. This review provides a comprehensive analysis of the evolution, applications, challenges, and future outlook of clinical-grade AI in healthcare. We trace AI’s trajectory from early expert systems to contemporary deep learning and foundation models, highlighting milestones such as FDA-approved diagnostic devices and AI-driven clinical decision support. Current applications span medical imaging, predictive analytics, precision medicine, robotic surgery, and patient engagement tools. Despite its promise, widespread integration faces barriers including data quality, generalizability, ethical and regulatory complexities, and clinician trust. Moreover, AI adoption necessitates workforce transformation, emphasizing interdisciplinary skills, explain ability, and equitable access. Looking ahead, the field is shifting toward multimodal architectures, autonomous decision-making and system-level integration across healthcare ecosystems. Ultimately, clinical-grade AI is poised not to replace clinicians, but to augment their expertise, reduce administrative burdens, and advance equitable, patient-centered care.
Cite this article:
Nikhil M. Patil, Prashant R. Wagh, Anand G. Gavale, Chetan J. Girase. From Hype to Healing: A Comprehensive Review of Clinical Grade AI in Modern Healthcare Systems. Asian Journal of Research in Pharmaceutical Sciences. 2026; 16(1):31-8. doi: 10.52711/2231-5659.2026.00006
Cite(Electronic):
Nikhil M. Patil, Prashant R. Wagh, Anand G. Gavale, Chetan J. Girase. From Hype to Healing: A Comprehensive Review of Clinical Grade AI in Modern Healthcare Systems. Asian Journal of Research in Pharmaceutical Sciences. 2026; 16(1):31-8. doi: 10.52711/2231-5659.2026.00006 Available on: https://www.ajpsonline.com/AbstractView.aspx?PID=2026-16-1-6
REFERENCE:
1. Davenport T and Kalakota R: The potential for artificial intelligence in healthcare. Future Healthc J. 2019; 6: 94 98.
2. Muthukrishnan N, Maleki F, Ovens K, Reinhold C, Forghani B and Forghani R: Brief History of Artificial Intelligence. Neuroimaging Clin N Am. 2020; 30: 393 399.
3. Fogel AL and Kvedar JC: Artificial intelligence powers digital medicine. NPJ Digit Med. 2018; 1: 5.
4. Yu KH, Beam AL and Kohane IS: Artificial intelligence in healthcare. Nat Biomed Eng. 2018; 2: 719 731.
5. Rajpurkar P, Chen E, Banerjee O and Topol EJ: AI in health and medicine. Nat Med. 2022; 28: 31 38.
6. Polevikov S: Advancing AI in healthcare: A comprehensive review of best practices. ClinChimActa. 2023; 548: 117519.
7. Akyon SH, Akyon FC, Yılmaz TE. Artificial intelligence-supported web application design and development for reducing polypharmacy side effects and sup porting rational drug use in geriatric patients. Front Med. 2023; 10: 1029198. doi:10.3389/fmed.2023.1029198
8. Ahuja AS. The impact of artificial intelligence in medicine on the future role of the physician. Peer J. 2019; 7: e7702. doi:10.7717/peerj.7702
9. Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gas trointestEndosc. 2020;92:807-812
10. Amisha, Malik P, Pathania M, Rathaur VK. Overview of artificial intelligence in medicine. J Fam Med Prim Care. 2019; 8: 2328-2331.
11. We're past the excitement phase—AI is in the exam room now- Dr. Eric Topol, 2024
12. Shortliffe, E. H. (1976). Computer-based medical consultations: MYCIN. Elsevier.
13. Patel, V. L., et al. The coming of age of artificial intelligence in medicine. Artificial Intelligence in Medicine. 2009; 46(1): 5–17.
14. Gulshan, V., et al. (). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA. 2016; 316(22): 2402–2410.
15. Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine. 2019; 25(1): 44–56.
16. Singhal, K., et al. Large language models encode clinical knowledge. Nature. 2023; 616(7956): 259–264.
17. Moor, M., et al. Foundation models for generalist medical artificial intelligence. Nature. 2023; 616(7956): 259–264.
18. Sendak, M. P., et al. (). A path for translation of machine learning products into healthcare delivery. NPJ Digital Medicine. 2020; 3: 90.
19. Shickel, B., et al. Deep EHR: A survey of recent advances in deep learning techniques for electronic health record (EHR) analysis. IEEE Journal of Biomedical and Health Informatics. 2018; 22(5): 1589–1604.
20. Jiang, F., et al. Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology. 2017; 2(4): 230–243.
21. Miner, A. S., et al. Smartphone-based conversational agents and responses to questions about mental health, interpersonal violence, and physical health. JAMA Internal Medicine. 2016; 176(5): 619–625.
22. Hashimoto, D. A., et al. Artificial intelligence in surgery: promises and perils. Annals of Surgery. 2018; 268(1): 70–76.
23. FDA (2019). Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning-Based Software as a Medical Device (SaMD). U.S. Food and Drug Administration.
24. European Commission. (2021). Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act).
25. WHO (2021). Ethics and governance of artificial intelligence for health. World Health Organization.
26. Abràmoff, M. D., et al. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. npj Digital Medicine. 2018; 1: 39.
27. Beam, A. L., and Kohane, I. S. Big data and machine learning in health care. JAMA. 2018; 319(13): 1317–1318.
28. Finlayson, S. G., et al. The clinician and dataset shift in artificial intelligence. New England Journal of Medicine. 2021; 385(3): 283–286.
29. He, J., et al. The practical implementation of artificial intelligence technologies in medicine. Nature Medicine. 2019; 25(1): 30–36.
30. Samek, W., et al. (2017). Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models. arXiv preprint arXiv:1708.08296.
31. U.S. Food and Drug Administration (FDA). (2019). Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning-Based Software as a Medical Device (SaMD).
32. Leslie, D. (2019). Understanding artificial intelligence ethics and safety. The Alan Turing Institute.
33. Topol, E. J. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.
34. Jiang, F., et al. Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology. 2017; 2(4): 230–243.
35. Mesko, B., et al. Digital health is a cultural transformation of traditional healthcare. mHealth. 2020; 6: 15.
36. He, J., et al. The practical implementation of artificial intelligence technologies in medicine. Nature Medicine. 2019; 25(1): 30–36.
37. Verghese, A., Shah, N. H., and Harrington, R. A. What this computer needs is a physician: humanism and artificial intelligence. JAMA. 2018; 319(1): 19–20.
38. World Health Organization (WHO). (2021). Ethics and governance of artificial intelligence for health.
39. https://www.theguardian.com/technology/2025/jun/30/microsoft-ai-system-better-doctors-diagnosing-health-conditions-research
40. https://www.theguardian.com/technology/2025/aug/16/nhs-to-trial-ai-tool-that-speeds-up-hospital-discharges
41. https://www.theguardian.com/technology/2025/aug/16/nhs-to-trial-ai-tool-that-speeds-up-hospital-discharges
42. https://timesofindia.indiatimes.com/city/delhi/iit-delhi-gets-centre-of-excellence-in-precision-and-personalised-healthcare/articleshow/123307367.cms