Author(s):
Tin Moe Nwe, Nur Amni Husna Shamshol1, Nurul Najwa Jaafar, Syazril Hafiy Syahruddin, Tariq Ahmad Yusaini, Tuan Fatma Nadhirah Tuan Saha’Arif, Soe Lwin, Khin Than Yee, Myat San Yi, Swe Swe Latt
Email(s):
tinmoenwe@unikl.edu.my
DOI:
10.52711/0974-360X.2025.00358
Address:
Tin Moe Nwe1, Nur Amni Husna Shamshol1, Nurul Najwa Jaafar1, Syazril Hafiy Syahruddin1, Tariq Ahmad Yusaini1 , Tuan Fatma Nadhirah Tuan Saha’Arif1 , Soe Lwin1, Khin Than Yee1, Myat San Yi2, Swe Swe Latt3
1Faculty of Medicine, Royal College of Medicine Perak, Universiti Kuala Lumpur, Ipoh, Perak, Malaysia.
2Suri Seri Begawan Hospital, Kuala Belait, Brunei.
3Department of Public Health Medicine, RCSI & UCD Malaysia Campus, RUMC, Penang, Malaysia.
*Corresponding Author
Published In:
Volume - 18,
Issue - 6,
Year - 2025
ABSTRACT:
Introduction: Artificial intelligence (AI) is revolutionizing medical education by enhancing learning experiences, improving knowledge retention, and providing personalized guidance. Through interactive simulations, virtual tutors, and adaptive learning platforms, AI-powered solutions help students in preclinical education grasp difficult ideas. Thus this study aims to examine the impact of AI on preclinical medical education students' academic performance, engagement, and readiness for clinical training among preclinical medical students, examining its applicability, efficacy, potential, and limitations. Which is done by outlining the objectives and evaluating the effectiveness, opportunities, and challenges of integrating artificial intelligence (AI) tools in medical education among Year 1 and Year 2 MBBS students in a private medical university, Malaysia. Methodology: The study involved 300 sample population, including 152 Year 1 and 148 Year 2 students. A cross-sectional questionnaire-based study was conducted, with a sample size of 184 with a 95% confidence level. Data were collected through online surveys and analysis using Microsoft Excel and IBM SPSS version 23.0.Result: All 184 preclinical students used AI tools in their medical education, mainly relying on ChatGPT. About 84.2% are familiar with AI in this context. The effectiveness of AI in improving learning was rated from 1 to 3, with most students scoring AI as 4 or 5 in problem-solving, decision-making, critical thinking, and inspiring new ideas, indicating a high perception of its effectiveness. Many believe AI supports traditional teaching. However, concerns exist about over-reliance on technology (83.2%) and loss of critical thinking skills (77.7%). Also, 42.9% rated their worries about AI's impact on clinical decision-making skills as a 3. Conclusion: Most preclinical students know about AI in medical education and believe it helps improve learning. AI assists students in solving problems, making decisions, encouraging critical thinking, and generating new ideas. However, concerns felt about much dependence on technology and weaken critical thinking skills in medical education. Students believe that AI will not entirely harm clinical decision-making skills. In summary, AI offers both advantages and disadvantages in medical education.
Cite this article:
Tin Moe Nwe, Nur Amni Husna Shamshol1, Nurul Najwa Jaafar, Syazril Hafiy Syahruddin, Tariq Ahmad Yusaini, Tuan Fatma Nadhirah Tuan Saha’Arif, Soe Lwin, Khin Than Yee, Myat San Yi, Swe Swe Latt. The Role of Artificial intelligence in Medical training, with its Applicability, Efficiency, Potential, and Challenges among Preclinical Students. Research Journal of Pharmacy and Technology. 2025;18(6):2508-6. doi: 10.52711/0974-360X.2025.00358
Cite(Electronic):
Tin Moe Nwe, Nur Amni Husna Shamshol1, Nurul Najwa Jaafar, Syazril Hafiy Syahruddin, Tariq Ahmad Yusaini, Tuan Fatma Nadhirah Tuan Saha’Arif, Soe Lwin, Khin Than Yee, Myat San Yi, Swe Swe Latt. The Role of Artificial intelligence in Medical training, with its Applicability, Efficiency, Potential, and Challenges among Preclinical Students. Research Journal of Pharmacy and Technology. 2025;18(6):2508-6. doi: 10.52711/0974-360X.2025.00358 Available on: https://rjptonline.org/AbstractView.aspx?PID=2025-18-6-11
REFERENCES:
1. McCarthy J, Minsky ML, Rochester N, Shannon CE. A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI Magazine. 2006 Dec 15; 27(4): 12.
2. Zheng K, Shen Z, Chen Z, Che C, Zhu H. Application of AI-empowered scenario-based simulation teaching mode in cardiovascular disease education. BMC Medical Education. 2024 Sep 13; 24(1): 1003.
3. Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR medical education. 2019 Jun 14; 5(1): e13930.
4. Paranjape K, Schinkel M, Panday RN, Car J, Nanayakkara P. Introducing artificial intelligence training in medical education. JMIR medical education. 2019 Dec 3; 5(2):e16048.
5. Briganti G, Le Moine O. Artificial intelligence in medicine: today and tomorrow. Frontiers in medicine. 2020 Feb 5; 7: 509744.
6. Masters K. Artificial intelligence in medical education. Medical Teacher. 2019 Sep 2; 41(9):976-80.
7. Lee J, Wu AS, Li D, Kulasegaram KM. Artificial intelligence in undergraduate medical education: a scoping review. Academic Medicine. 2021 Nov 1; 96(11S):S62-70.
8. Weidener, L. and Fischer, M., 2024. Artificial intelligence in medicine: cross-sectional study among medical students on application, education, and ethical aspects. JMIR Medical Education, 10(1), p.e51247.Z
9. Azer SA, Guerrero AP. The challenges imposed by artificial intelligence: are we ready in medical education?. BMC Medical Education. 2023 Sep 19; 23(1):680.
10. Ramakrishnan L. A Framework for Effective Risk Assessment of AI-Biotechnology Convergence.
11. Civaner MM, Uncu Y, Bulut F, Chili EG, Tatli A. Artificial intelligence in medical education: a cross-sectional needs assessment. BMC Medical Education. 2022 Nov 9; 22(1):772.
12. Zhang W, Cai M, Lee HJ, Evans R, Zhu C, Ming C. AI in Medical Education: Global situation, effects and challenges. Education and Information Technologies. 2024 Mar; 29(4):4611-33
13. Sapci AH, Sapci HA. Artificial intelligence education and tools for medical and health informatics students: systematic review. JMIR Medical Education. 2020 Jun 30; 6(1):e19285.
14. Feigerlova E, Hani H, Hothersall-Davies E. A systematic review of the impact of artificial intelligence on educational outcomes in health professions education. BMC Medical Education. 2025 Jan 27; 25(1):129.
15. Guerrero-Quiñonez AJ, Bedoya-Flores MC, Mosquera-Quiñonez EF, Mesías-Simisterra ÁE, Bautista-Sánchez JV. Artificial Intelligence and its scope in Latin American higher education. Ibero-American Journal of Education and Society Research. 2023 May 30; 3(1):264-71.
16. Mir MM, Mir GM, Raina NT, Mir SM, Mir SM, Miskeen E, Alharthi MH, Alamri MM. Application of artificial intelligence in medical education: current scenario and future perspectives. Journal of Advances in Medical Education and Professionalism. 2023 Jul; 11(3):133.
17. Zarei M, Mamaghani HE, Abbasi A, Hosseini MS. Application of artificial intelligence in medical education: a review of benefits, challenges, and solutions. Medicina Clínica Práctica. 2024 Apr 1; 7(2):100422.