With the rapid development of generative AI (GenAI) technology, its application in the field of surgical teaching becomes increasingly important. This article reviews the applications of GenAI in surgical professional education areas such as surgery video analysis, robotic surgery assistance, surgical skills training, clinical thinking development, virtual standardized patient (SP) interaction, personalized learning path design, knowledge graph integration, multimodal learning experience construction, and digital twin technology simulation. At the same time, the article also explores the ethical, legal, and social issues that accompany the application of these technologies, as well as the challenges of the technologies themselves and the directions for future development.
Chen Jiancong
,
Zhang Kunsong
,
Huang Xitai
,
Zhang Yunjian
,
Feng Shaoting
,
Kuang Ming
. Applications and challenges of generative artificial intelligence in surgical teaching[J]. Chinese Journal of Medical Education, 2025
, 45(3)
: 167
-173
.
DOI: 10.3760/cma.j.cn115259-20240529-00542
[1] Stokel-Walker C, Van Noorden R. What ChatGPT and generative AI mean for science[J]. Nature, 2023,614(7947):214-216. DOI: 10.1038/d41586-023-00340-6.
[2] Mesko B. The ChatGPT (generativeartificial intelligence) revolution has made artificial intelligence approachable for medical professionals[J]. J Med Internet Res, 2023,25:e48392. DOI: 10.2196/48392.
[3] Boscardin CK, Gin B, Golde PB, et al. ChatGPT and generative artificial intelligence for medical education: potential impact and opportunity[J]. Acad Med, 2024,99(1):22-27. DOI: 10.1097/ACM.0000000000005439.
[4] Madani A, Namazi B, Altieri MS, et al. Artificial intelligence for intraoperative guidance: using semantic segmentation to identify surgical anatomy during laparoscopic cholecystectomy[J]. Ann Surg, 2022,276(2):363-369. DOI: 10.1097/SLA.0000000000004594.
[5] Cheng Q, Dong Y. Da Vinci Robot-assisted video image processing under artificial intelligence vision processing technology[J]. Comput Math Methods Med, 2022,2022:2752444. DOI: 10.1155/2022/2752444.
[6] Nagaraj MB, Namazi B, Sankaranarayanan G, et al. Developing artificial intelligence models for medical student suturing and knot-tying video-based assessment and coaching[J]. Surg Endosc, 2023,37(1):402-411. DOI: 10.1007/s00464-022-09509-y.
[7] Loftus TJ, Tighe PJ, Filiberto AC, et al. Artificial intelligence and surgical decision-making[J]. JAMA Surg, 2020,155(2):148-158. DOI: 10.1001/jamasurg.2019.4917.
[8] Wang L, Chen X, Zhang L, et al. Artificial intelligence in clinical decision support systems for oncology[J]. Int J Med Sci, 2023,20(1):79-86. DOI: 10.7150/ijms.77205.
[9] 邓学鹏. 人工智能与临床医师决策乳腺癌患者术后辅助治疗同CSCO指南的一致性研究[D]. 昆明: 昆明医科大学, 2023.
[10] 韩春光. 人工智能临床决策支持系统在Ⅰ-Ⅲ期乳腺癌术后辅助治疗中的应用性研究[D]. 合肥: 安徽医科大学, 2023.
[11] Berman NB, Durning SJ, Fischer MR, et al. The role for virtual patients in the future of medical education[J]. Acad Med, 2016,91(9):1217-1222. DOI: 10.1097/ACM.0000000000001146.
[12] Sabzwari SR, Ishaque S, Memon SJ, et al. Creation of virtual patients for undergraduate and postgraduate medical education: an experience from Pakistan[J]. J Coll Physicians Surg Pak, 2023,33(4):457-459. DOI: 10.29271/jcpsp.2023.04.457.
[13] Wei X, Sun S, Wu D, et al. Personalized online learning resource recommendation based on artificial intelligence and educational psychology[J]. Front Psychol, 2021,12:767837. DOI: 10.3389/fpsyg.2021.767837.
[14] Daungsupawong H, Wiwanitkit V. Knowledge-map analysis and bladder cancer immunotherapy: comment[J]. Hum Vaccin Immunother, 2023,19(3):2285094. DOI: 10.1080/21645515.2023.2285094.
[15] Zhang J, Yu X, Xie Z, et al. A bibliometric and knowledge-map analysis of antibody-mediated rejection in kidney transplantation[J]. Ren Fail, 2023,45(2):2257804. DOI: 10.1080/0886022X.2023.2257804.
[16] Hou J, Lv Z, Wang Y, et al. Knowledge-map analysis of percutaneous nephrolithotomy (PNL) for urolithiasis[J]. Urolithiasis, 2023,51(1):34. DOI: 10.1007/s00240-023-01406-w.
[17] Mergen M, Meyerheim M, Graf N. Reviewing the current state of virtual reality integration in medical education - a scoping review protocol[J]. Syst Rev, 2023,12(1):97. DOI: 10.1186/s13643-023-02266-6.
[18] Ahmed H, Devoto L. The potential of a digital twin in surgery[J]. Surg Innov, 2021,28(4):509-510. DOI: 10.1177/1553350620975896.
[19] Thiong′o GM, Rutka JT. Digital twin technology: the future of predicting neurological complications of pediatric cancers and their treatment[J]. Front Oncol, 2021,11:781499. DOI: 10.3389/fonc.2021.781499.
[20] Gradon KT. Generative artificial intelligence and medical disinformation[J]. BMJ, 2024,384:q579. DOI: 10.1136/bmj.q579.
[21] Nguyen A, Ngo HN, Hong Y, et al. Ethical principles for artificial intelligence in education[J]. Educ Inf Technol (Dordr), 2023,28(4):4221-4241. DOI: 10.1007/s10639-022-11316-w.
[22] Preiksaitis C, Rose C. Opportunities, challenges, and future directions of generative artificial intelligence in medical education: scoping review[J]. JMIR Med Educ, 2023,9:e48785. DOI: 10.2196/48785.