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Dr. Danasegaran M
Dr. Shilpa T Patil
Dr. M. Thirumaran
Dr. P.V.Balaji


Artificial intelligence, Medical students, Health care technology.


Introduction: Artificial intelligence (AI) encompasses technologies that mimic human intelligence, including speech recognition, decision-making, and visual perception. Its applications in healthcare range from drug development and medical imaging to tailored treatment regimens and predictive analytics. AI improves efficiency and patient care by assisting clinicians and enabling telemedicine. However, its widespread adoption depends on a deep understanding of AI among medical students, highlighting the need for AI-focused education to foster innovation in healthcare.

Materials and Methods: This descriptive cross-sectional study, conducted at a tertiary care teaching hospital, surveyed final MBBS students' knowledge, attitudes, and practices toward artificial intelligence (AI) in healthcare. Approved by the Institutional Ethics Committee, the study used Google Forms to collect 79 complete responses over a 15-day period. The questionnaire assessed students' AI knowledge through 7 yes/no items, attitudes with 10 items rated from 'strongly disagree' to 'strongly agree,' and practices using 7 items rated from 'never' to 'always.

Results:The study found that 55 out of 79 (69.62%) respondents were female, while 24 (30.38%) were male. Notably, 70.3% lacked solid AI knowledge, and 72.2% were unfamiliar with deep learning/machine learning concepts. Only 5.4% attended AI-related courses, indicating a gap in AI education among medical students. Although most students had a neutral attitude toward AI, 43.2% agreed healthcare students should learn AI basics. In practice, AI usage was low, with 41.7% "never" using AI for exam preparation and 43.2% for homework/assignments.

Conclusion: the findings suggest that while medical students show interest in AI, there is a lack of comprehensive education and training in AI, leading to minimal use in practice. The study underscores the need for enhanced AI education and practical exposure to better prepare medical students for the evolving healthcare landscape.

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1. Sapci AH, Sapci HA. Artificial Intelligence Education and Tools for Medical and Health Informatics Students: Systematic Review JMIR Med Educ 2020;6(1):e19285 doi: 10.2196/19285.
2. Perrier E, Rifai M, Terzic A, Dubois C, Cohen JF. Knowledge, attitudes, and practices towards artificial intelligence among young pediatricians: A nationwide survey in France. Front Pediatr. 2022;10:1065957. doi: 10.3389/fped.2022.1065957. PMID: 36619510; PMCID: PMC9816325
3. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang X. The practical implementation of artificial intelligence technologies in medicine. Nat Med. 2019;25(1):30-36.doi: 10.1038/s41591-018-0307-0
4. Shorey S, Ang E, Yap J, Ng ED, Lau ST, Chui CK. A virtual counseling application using Artificial Intelligence for Communication Skills Training in nursing education: Development Study. J Med Internet Res. 2019;21(10):e14658
5. James CA, Wachter RM, Woolliscroft JO. Preparing clinicians for a clinical world influenced by artificial intelligence. JAMA.2022;327(14):1333–4. 10.1001/jama.2022.3580
6. Popenici S.A., Kerr S. Exploring the impact of artificial intelligence on teaching and learning in higher education. Research Res. Pract. Technol. Enhanc. Learn. 2017;12(1):1–13.
7. Bayne S. Teacherbot: interventions in automated teaching. Teach. High. Educ. 2015;20(4):455–467.
8. Popenici SA, Kerr S. Exploring the impact of artificial intelligence on teaching and learning in higher education. Res PractTechnolEnhanc Learn. 2017;12(1):22.
9. Al-Qerem W, Eberhardt J, Jarab A, et al. Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions’ students in Jordan. BMC Med Inform DecisMak. 2023;23(1):288. doi: 10.1186/s12911-023-02403-0
10. CaparrósGalán G, SendraPortero F. Medical students’ perceptions of the impact of artificial intelligence in radiology. Percepciones de estudiantes de medicinasobre el impacto de la inteligencia artificial enradiología. Radiologia. 2021;63(5):419-426. doi: 10.1016/j.rx.2021.03.006.
11. Pinto Dos Santos D, Giese D, Brodehl S, et al. Medical students’ attitude towards artificial intelligence: a multicentre survey. EurRadiol. 2019;29(4):1640–1646. Doi:10.1007/s00330-018-5601-1.
12. Mehta N, Harish V, Bilimoria K, et al. Knowledge and Attitudes on Artificial Intelligence in Healthcare: A Provincial Survey Study of Medical Students. MedEdPublish. 2021;10(1):75. doi: 10.15694/mep.2021.000075.1
13. Topol EJ: High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019, 25:44-56.
14. Zhang Y, Luo M, Wu P, Wu S, Lee TY, Bai C: Application of computational biology and artificial intelligence in drug design. Int J Mol Sci. 2022, 23:10.3390/ijms232113568
15. Ahmed Z, Bhinder KK, Tariq A, et al. Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Pakistan: a cross-sectional online survey. Ann Med Surg (Lond). 2022;76:103493. doi: 10.1016/j.amsu.2022.103493.