Journal of Medicine and Life Science

  • 제20권2호
  • /
  • Pages.53-59
  • /
  • 2023
  • /
  • 1738-1010(pISSN)
  • /
  • 2671-4922(eISSN)
제주대학교 의과학연구소 (Institute for Medical Science)
권호 표지
DOI QR코드

DOI QR Code

의학 교육에서 인공지능의 응용: 임상의학 교육을 위한 ChatGPT의 활용을 중심으로

Application of artificial intelligence in medical education: focus on the application of ChatGPT for clinical medical education

  • 홍현미 (서울대학교 교육종합연구원) ;
  • 강영준 (제주대학교 의과대학 의학교육학교실) ;
  • 김영전 (원광대학교 의과대학 의학교육학교실) ;
  • 김봄솔 (NSPACE 개발팀)
  • Hyeonmi Hong (The Center for Educational Research, Seoul National University) ;
  • Youngjoon Kang (Department of Medical Education, Jeju National University College of Medicine) ;
  • Youngjon Kim (Department of Medical Education, Wonkwang University School of Medicine) ;
  • Bomsol Kim (Development Team, NSPACE)
  • 투고 : 2023.05.24
  • 심사 : 2023.06.21
  • 발행 : 2023.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This study explores the potential use of artificial intelligence (AI)-based services, specifically ChatGPT-3.5, in medical education. The application of this technology is acknowledged as a valuable tool for simulating authentic clinical scenarios and enhancing learners' diagnostic and communication skills. To construct a case, students received ChatGPT training using a clinical ethics casebook titled "Clinical Ethics Cases and Commentaries for Medical Students and Physicians." Subsequently, a role-play script was generated based on this training. The initial draft of the script was reviewed by two medical professors and was further optimized using ChatGPT-3.5. Consequently, a comprehensive role-play script, accurately reflecting real-world clinical situations, was successfully developed. This study demonstrates the potential for effectively integrating AI technology into medical education and provides a solution to overcome limitations in developing role-play scripts within conventional educational settings. However, the study acknowledges that AI cannot always generate flawless role-play scripts and recognizes the necessity of addressing these limitations and ethical concerns. The research explores both the potential and limitations of employing AI in the early stages of medical education, suggesting that future studies should focus on overcoming these limitations while further investigating the potential applications of AI in this field.

키워드

과제정보

이 논문은 2020년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구이다(NRF-2020S1A5B5A16084033).

참고문헌

  1. Paranjape K, Schinkel M, Nannan Panday R, Car J, Nanayakkara P. Introducing artificial intelligence training in medical education. JMIR Med Educ 2019;5:e16048. 
  2. Rampton V, Mittelman M, Goldhahn J. Implications of artificial intelligence for medical education. Lancet Digit Health 2020;2:e111-2.  https://doi.org/10.1016/S2589-7500(20)30023-6
  3. Wartman SA, Combs CD. Medical education must move from the information age to the age of artificial intelligence. Acad Med 2018;93:1107-9.  https://doi.org/10.1097/ACM.0000000000002044
  4. Cope B, Kalantzis M, Zhai CX, Krussel A, Searsmith D, Ferguson D, et al. Maps of medical reason: applying knowledge graphs and artificial intelligence in medical education and practice. In: Peters MA, Jandric P, Hayes S, editors. Bioinformational philosophy and postdigital knowledge ecologies. Cham: Springer; 2022. pp. 133-59. 
  5. Arif TB, Munaf U, Ul-Haque I. The future of medical education and research: is ChatGPT a blessing or blight in disguise? Med Educ Online 2023;28:2181052. 
  6. Lee P, Bubeck S, Petro J. Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine. N Engl J Med 2023;388:1233-9.  https://doi.org/10.1056/NEJMsr2214184
  7. Ahuja AS, Polascik BW, Doddapaneni D, Byrnes ES, Sridhar J. The digital metaverse: applications in artificial intelligence, medical education, and integrative health. Integr Med Res 2023;12:100917. 
  8. Khan RA, Jawaid M, Khan AR, Sajjad M. ChatGPT - Reshaping medical education and clinical management. Pak J Med Sci 2023;39:605-7.  https://doi.org/10.12669/pjms.39.2.7653
  9. Eysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers. JMIR Med Educ 2023;9:e46885. 
  10. Uunona GN, Goosen L. Leveraging ethical standards in artificial intelligence technologies: a guideline for responsible teaching and learning applications. In: Garcia MB, Cabrera MVL, de Almeida RPP, editors. Handbook of research on instructional technologies in health education and allied disciplines. Hershey: IGI Global; 2023. pp. 310-30. 
  11. Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Med Educ 2019;5:e13930. 
  12. Park SH, Do KH, Kim S, Park JH, Lim YS. What should medical students know about artificial intelligence in medicine? J Educ Eval Health Prof 2019;16:18. 
  13. Lee H. The rise of ChatGPT: exploring its potential in medical education. Anat Sci Educ 2023. (Epub ahead of print) 
  14. Winkler-Schwartz A, Bissonnette V, Mirchi N, Ponnudurai N, Yilmaz R, Ledwos N, et al. Artificial intelligence in medical education: best practices using machine learning to assess surgical expertise in virtual reality simulation. J Surg Educ 2019;76:1681-90.  https://doi.org/10.1016/j.jsurg.2019.05.015
  15. Valikodath NG, Cole E, Ting DSW, Campbell JP, Pasquale LR, Chiang MF, et al. Impact of artificial intelligence on medical education in ophthalmology. Transl Vis Sci Technol 2021;10:14. 
  16. Hu R, Fan KY, Pandey P, Hu Z, Yau O, Teng M, et al. Insights from teaching artificial intelligence to medical students in Canada. Commun Med (Lond) 2022;2:63. 
  17. Sallam M, Salim NA, Barakat M, Al-Tammemi AB. ChatGPT applications in medical, dental, pharmacy, and public health education: a descriptive study highlighting the advantages and limitations. Narra J 2023;3:e103. 
  18. Park CJ, Yi PH, Siegel EL. Medical student perspectives on the impact of artificial intelligence on the practice of medicine. Curr Probl Diagn Radiol 2021;50:614-9.  https://doi.org/10.1067/j.cpradiol.2020.06.011
  19. McCoy LG, Nagaraj S, Morgado F, Harish V, Das S, Celi LA. What do medical students actually need to know about artificial intelligence? NPJ Digit Med 2020;3:86. 
  20. Garg T. Artificial intelligence in medical education. Am J Med 2020;133:e68. 
  21. Nestel D, Tierney T. Role-play for medical students learning about communication: guidelines for maximising benefits. BMC Med Educ 2007;7:3. 
  22. Bokken L, Linssen T, Scherpbier A, van der Vleuten C, Rethans JJ. Feedback by simulated patients in undergraduate medical education: a systematic review of the literature. Med Educ 2009;43:202-10.  https://doi.org/10.1111/j.1365-2923.2008.03268.x
  23. Lane C, Rollnick S. The use of simulated patients and role-play in communication skills training: a review of the literature to August 2005. Patient Educ Couns 2007;67:13-20.  https://doi.org/10.1016/j.pec.2007.02.011
  24. Cleland JA, Abe K, Rethans JJ. The use of simulated patients in medical education: AMEE guide No. 42. Med Teach 2009;31:477-86.  https://doi.org/10.1080/01421590903002821
  25. Kim OJ, Kim HJ, Moon KU, Jung JH. Clinical ethics cases for medical students and general physicians. Seoul: Department of History Medicine & Medical Humanities of Seoul National University College of Medicine; 2020. 
  26. Jung JS. Current status and future direction of artificial intelligence in healthcare and medical education. Korean Med Educ Rev 2020;22:99-114.  https://doi.org/10.17496/kmer.2020.22.2.99
  27. Yeh BI. Bedside education will be more important than now in the age of artificial intelligence. KMER 2016;18:58-64.  https://doi.org/10.17496/KMER.2016.18.2.58
  28. Biswas S. ChatGPT and the future of medical writing. Radiology 2023;307:e223312. 
  29. Gong B, Nugent JP, Guest W, Parker W, Chang PJ, Khosa F, et al. Influence of artificial intelligence on Canadian medical students' preference for radiology specialty: a national survey study. Acad Radiol 2019;26:566-77.  https://doi.org/10.1016/j.acra.2018.10.007
  30. Sit C, Srinivasan R, Amlani A, Muthuswamy K, Azam A, Monzon L, et al. Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey. Insights Imaging 2020;11:14. 
  31. Barreiro-Ares A, Morales-Santiago A, Sendra-Portero F, Souto-Bayarri M. Impact of the rise of artificial intelligence in radiology: what do students think? Int J Environ Res Public Health 2023;20:1589. 
  32. Wang C, Xie H, Wang S, Yang S, Hu L. Radiological education in the era of artificial intelligence: a review. Medicine (Baltimore) 2023;102:e32518. 
  33. Ossa LA, Rost M, Lorenzini G, Shaw DM, Elger BS. A smarter perspective: learning with and from AI-cases. Artif Intell Med 2023;135:102458. 
  34. Zhao H, Li G, Feng W. Research on application of artificial intelligence in medical education. In: 2018 International Conference on Engineering Simulation and Intelligent Control (ESAIC); 2018 Aug 10-11; Hunan, China. pp. 340-2.