References
- Ahmad Z, Rahim S, Zubair M, Abdul-Ghafar J. 2021. Artificial intelligence (AI) in medicine, current applications and future role with special emphasis on its potential and promise in pathology: present and future impact, obstacles including costs and acceptance among pathologists, practical and philosophical considerations. A comprehensive review. Diagn Pathol. 16(1):24. doi:10.1186/s13000-021-01085-4.
- Alami H, Lehoux P, Auclair Y, de Guise M, Gagnon M-P, Shaw J, Roy D, Fleet R, Ag Ahmed MA, Fortin J-P, et al. 2020. Artificial intelligence and health technology assessment: anticipating a new level of complexity. J Med Internet Res. 22(7):e17707. doi:10.2196/17707.
- Çalışkan SA, Demir K, Karaca O. 2022. Artificial intelligence in medical education curriculum: an e-Delphi study for competencies. PLOS One. 17(7):e0271872. doi:10.1371/journal.pone.0271872.
- Chan KS, Zary N. 2019. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Med Educ. 5(1):e13930. doi:10.2196/13930.
- Civaner MM, Uncu Y, Bulut F, Chalil EG, Tatli A. 2022. Artificial intelligence in medical education: a cross-sectional needs assessment. BMC Med Educ. 22(1):772. doi:10.1186/s12909-022-03852-3.
- Dai C-P, Ke F. 2022. Educational applications of artificial intelligence in simulation-based learning: a systematic mapping review. Comput Educ Artif Intell. 3:100087.
- https://github.com/denovo2021/NMLE. 2021. National Medical Licensing Examination. Available from: https://github.com/denovo2021/NMLE.
- Flores-Cohaila JA, García-Vicente A, Vizcarra-Jiménez SF, De la Cruz-Galán JP, Gutiérrez-Arratia JD, Quiroga Torres BG, Taype-Rondan A. 2023. Performance of ChatGPT on the Peruvian National Licensing Medical Examination: cross-sectional study. JMIR Med Educ. 9:e48039. doi:10.2196/48039.
- Gilson A, Safranek CW, Huang T, Socrates V, Chi L, Taylor RA, Chartash D. 2023. How does ChatGPT perform on the United States Medical Licensing Examination? The implications of large language models for medical education and knowledge assessment. JMIR Med Educ. 9:e45312. doi:10.2196/45312.
- Hah H, Goldin DS. 2021. How clinicians perceive artificial intelligence-assisted technologies in diagnostic decision making: mixed methods approach. J Med Internet Res. 23(12):e33540. doi:10.2196/33540.
- Haug CJ, Drazen JM. 2023. Artificial intelligence and machine learning in clinical medicine, 2023. N Engl J Med. 388(13):1201–1208. doi:10.1056/NEJMra2302038.
- Huang J, Neill L, Wittbrodt M, Melnick D, Klug M, Thompson M, Bailitz J, Loftus T, Malik S, Phull A, et al. 2023. Generative artificial intelligence for chest radiograph interpretation in the Emergency Department. JAMA Netw Open. 6(10):e2336100. doi:10.1001/jamanetworkopen.2023.36100.
- Japan Ministry of Health, Labour and Welfare. 2018a. Questions and correct answers for the 112th National Medical Examination. Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/topics/tp180511-01.html.
- Japan Ministry of Health, Labour and Welfare. 2018b. Announcement of acceptance rate of the 112th National Medical Examination. Available from: https://www.mhlw.go.jp/stf/shingi2/0000197611.html.
- Japan Ministry of Health, Labour and Welfare. 2019a. Questions and correct answers for the 113th National Medical Examination. Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/topics/tp190415-01.html.
- Japan Ministry of Health, Labour and Welfare. 2019b. Announcement of acceptance rate of the 113th National Medical Examination [cited 2023 Nov 20]. Available from: https://www.mhlw.go.jp/stf/shingi2/0000197611_00001.html.
- Japan Ministry of Health, Labour and Welfare. 2019c. Report of the subcommittee to study the improvement of the Japanese National Medical Licensing Examination. Available from: https://www.mhlw.go.jp/content/10803000/000693879.pdf.
- Japan Ministry of Health, Labour and Welfare. 2020a. Questions and correct answers for the 114th National Medical Examination. Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/topics/tp200421-01.html.
- Japan Ministry of Health, Labour and Welfare. 2020b. Announcement of acceptance rate of the 114th National Medical Examination [cited 2023 Nov 20]. Available from: https://www.mhlw.go.jp/stf/shingi2/0000197611_00002.html.
- Japan Ministry of Health, Labour and Welfare. 2021a. Questions and correct answers for the 115th National Medical Examination. Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/topics/tp210416-01.html.
- Japan Ministry of Health, Labour and Welfare. 2021b. Announcement of acceptance rate of the 115th National Medical Examination [cited 2023 Nov 20]. Available from: https://www.mhlw.go.jp/stf/shingi2/0000197611_00003.html.
- Japan Ministry of Health, Labour and Welfare. 2022a. Questions and correct answers for the 116th National Medical Examination. Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/topics/tp220421-01.html.
- Japan Ministry of Health, Labour and Welfare. 2022b. Announcement of acceptance rate of the 116th National Medical Examination [cited 2023 Nov 20]. Available from: https://www.mhlw.go.jp/stf/shingi2/0000197611_00004.html.
- Japan Ministry of Health, Labour and Welfare. 2023a. Questions and correct answers for the 117th National Medical Examination. Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/topics/tp230502-01.html.
- Japan Ministry of Health, Labour and Welfare. 2023b. Announcement of successful passage of the 117th National Medical Examination. Available from: https://www.mhlw.go.jp/general/sikaku/successlist/2023/siken01/about.html.
- Japan Ministry of Health Labour and Welfare. 2023c. Announcement of acceptance rate of the 117th National Medical Examination [cited 2023 Nov 20]. Available from: https://www.mhlw.go.jp/stf/shingi2/0000197611_00006.html.
- Kumar Y, Koul A, Singla R, Ijaz MF. 2023. Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda. J Ambient Intell Human Comput. 14(7):8459–8486. doi:10.1007/s12652-021-03612-z.
- Kung TH, Cheatham M, Medenilla A, Sillos C, De Leon L, Elepaño C, Madriaga M, Aggabao R, Diaz-Candido G, Maningo J, et al. 2023. Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models. PLOS Digit Health. 2(2):e0000198. doi:10.1371/journal.pdig.0000198.
- MEC. 2023. MEC National Medical Licensing Examination Bulletin Board. Available from: https://bbs.icrip.jp/.
- Medic Media. 2022. The 116th National Medical Licensing Examination [contraindicated questions]. @medicmedia_; [updated 2022 Apr 6]. Available from: https://informa.medilink-study.com/web-informa/post36171.html/.
- Mir MM, Mir GM, Raina NT, Mir SM, Mir SM, Miskeen E, et al. 2023. Application of artificial intelligence in medical education: current scenario and future perspectives. J Adv Med Educ Prof. 11(3):133–140.
- Moor M, Banerjee O, Abad ZSH, Krumholz HM, Leskovec J, Topol EJ, Rajpurkar P. 2023. Foundation models for generalist medical artificial intelligence. Nature. 616(7956):259–265. doi:10.1038/s41586-023-05881-4.
- Naithani N, Vasudevan B. 2021. Paradigm shift in medical education: the future beckons. Med J Armed Forces India. 77(Suppl 1):S1–S3. doi:10.1016/j.mjafi.2021.01.021.
- Office of Educational Technology. 2023. Artificial intelligence and the future of teaching and learning. Available from: https://www2.ed.gov/documents/ai-report/ai-report.pdf.
- Open AI I. 2022. GPT-4: @OpenAI. Available from https://openai.com/gpt-4.
- Open AI I. 2023. Vision-Lear how to use GPT-4 to understand images. Available from: https://platform.openai.com/docs/guides/vision.
- Sapci AH, Sapci HA. 2020. Artificial intelligence education and tools for medical and health informatics students: systematic review. JMIR Med Educ. 6(1):e19285. doi:10.2196/19285.
- Shafi S, Parwani AV. 2023. Artificial intelligence in diagnostic pathology. Diagn Pathol. 18(1):109. doi:10.1186/s13000-023-01375-z.
- Shokrollahi Y, Yarmohammadtoosky S, Nikahd MM, Dong P, Li X, Gu L. 2023. A comprehensive review of generative AI in Healthcare2023. arXiv:2310.00795. Available from: https://ui.adsabs.harvard.edu/abs/2023arXiv231000795S.
- Tolsgaard MG, Pusic MV, Sebok-Syer SS, Gin B, Svendsen MB, Syer MD, Brydges R, Cuddy MM, Boscardin CK. 2023. The fundamentals of artificial intelligence in medical education research: AMEE Guide No. 156. Med Teach. 45(6):565–573. doi:10.1080/0142159X.2023.2180340.
- Wang LK, Paidisetty PS, Cano AM. 2023. The next paradigm shift? ChatGPT, artificial intelligence, and medical education. Med Teach. 45(8):925–925. doi:10.1080/0142159X.2023.2198663.
- Wu W, Zhang B, Li S, Liu H. 2022. Exploring factors of the willingness to accept AI-assisted learning environments: an empirical investigation based on the UTAUT model and perceived risk theory. Front Psychol. 13:870777. doi:10.3389/fpsyg.2022.870777.
- Yanagita Y, Yokokawa D, Uchida S, Tawara J, Ikusaka M. 2023. Accuracy of ChatGPT on medical questions in the National Medical Licensing Examination in Japan: evaluation study. JMIR Form Res. 7:e48023. doi:10.2196/48023.