切换至 "中华医学电子期刊资源库"

中华肝脏外科手术学电子杂志 ›› 2025, Vol. 14 ›› Issue (06) : 822 -827. doi: 10.3877/cma.j.issn.2095-3232.2025.06.003

专家论坛

人工智能在肝胆外科临床教学中的应用
谢钰嵘, 唐流康, 陈明政, 王伟利, 缪文学, 谢峰()   
  1. 200438 海军军医大学第三附属医院(上海东方肝胆外科医院)胆道三科
  • 收稿日期:2025-05-18 出版日期:2025-12-10
  • 通信作者: 谢峰
  • 基金资助:
    上海市自然科学基金(16ZR1449200); 上海申康医院发展中心临床科技创新项目(SHDC12017X14); 上海申康医院发展中心临床研究型医师项目(SHDC2022CRD047); 教育部产学合作协同育人项目(230804810252616,230802368074710)

Application of artificial intelligence in clinical education of hepatobiliary surgery

Yurong Xie, Liukang Tang, Mingzheng Chen, Weili Wang, Wenxue Miu, Feng Xie()   

  1. Department Ⅲ of Biliary Tract Surgery, the Third Affiliated Hospital of Naval Military Medical University, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai 200438, China
  • Received:2025-05-18 Published:2025-12-10
  • Corresponding author: Feng Xie
引用本文:

谢钰嵘, 唐流康, 陈明政, 王伟利, 缪文学, 谢峰. 人工智能在肝胆外科临床教学中的应用[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(06): 822-827.

Yurong Xie, Liukang Tang, Mingzheng Chen, Weili Wang, Wenxue Miu, Feng Xie. Application of artificial intelligence in clinical education of hepatobiliary surgery[J/OL]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2025, 14(06): 822-827.

目前肝胆外科临床教学存在教学模式较为传统、学生临床操作能力不强等问题。而构建规范的肝胆外科临床教学模式,已成为教改发展的需求。因为肝胆疾病发病率高、临床实践中病例频繁出现,掌握相关知识对提高医学生临床诊治能力非常关键。然而,传统教学模式过于理论化,不利于学生掌握实际操作技能;又因肝胆外科疾病手术治疗复杂、操作难度较高,故需要采用有别于传统教学方法的新型教学模式。运用人工智能(AI)技术可以更高效地进行教学资源的整合,使用AI辅助设计问题驱动教学法等可培养学生临床思维,以及利用AI技术创建更加仿真的虚拟影像系统等工具提升学生对肝胆外科疾病的诊断能力。同时还需要强化手术操作训练,采用AI、虚拟仿真等技术,使学生在安全环境下掌握操作规范。总之,AI技术可以实现病例智能识别、虚拟仿真训练等,提高教学质量。

At present, multiple problems exist in clinical education of hepatobiliary surgery, such as traditional education mode and poor clinical operational capability of students, etc. Constructing standardized education models for hepatobiliary surgery has become the demand of educational reform and development. Considering high incidence of hepatobiliary diseases and frequent cases in clinical practice, mastering relevant knowledge plays a critical role in improving clinical treatment ability of medical students. However, traditional education mode is too theoretical to enable students to master practical skills. Besides, surgical treatment of hepatobiliary diseases is complicated and demanding, it is necessary to adopt a novel education mode different from traditional education method. Application of artificial intelligence (AI) can more efficiently integrate education resources. AI-aided design of problem-driven education method can cultivate students' clinical thinking. AI technology can be utilized to create a more simulated virtual imaging system and other tools to improve students' diagnostic capability of hepatobiliary diseases. In addition, it is necessary to strengthen surgical training and enable students to master operating norms in a safe environment using AI, virtual simulation and other technologies. Taken together, AI technology can realize intelligent case identification, virtual simulation training, and enhance education quality.

[1]
黄昂, 邹正升. 人工智能在肝脏疾病科临床教学中的应用[J]. 中国继续医学教育, 2023, 15(11): 141-145. DOI: 10.3969/j.issn.1674-9308.2023.11.032.
[2]
郑庆华. 人工智能赋能创建未来教育新格局[J]. 中国高教研究, 2024(3): 1-7. DOI: 10.16298/j.cnki.1004-3667.2024.03.01.
[3]
王立军, 李争平, 李颖, 等. 元宇宙终端: 虚拟(增强)现实关键硬科技发展趋势[J]. 科技导报, 2023, 41(15): 46-60. DOI: 10.3969/j.issn.1000-7857.2023.15.005.
[4]
王运武, 王永忠, 王藤藤, 等..元宇宙的起源、发展及教育意蕴[J] 中国医学教育技术, 2020, 34(1): 1-9. DOI: 10.13566/j.cnki.cmet.cn61-1317/g4.202202002.
[5]
董志涛, 方鲲鹏, 隋承军. PBL教学法联合文献检索学习在肝胆外科研究生培养中的应用[J]. 中国继续医学教育, 2021, 13(33): 26-29. DOI: 10.3969/j.issn.1674-9308.2021.33.007.
[6]
王巍, 张一范, 杨涛, 等. 微信平台PBL+CBL教学法在肝胆外科教学中的应用[J]. 中国继续医学教育, 2019, 11(19): 23-25. DOI: 10.3969/j.issn.1674-9308.2019.19.010.
[7]
蒋利锋, 谭延斌, 吴立东. 由学员引导的CBL联合PBL教学方法在骨科住院医师规范化培训中的应用[J]. 中国高等医学教育, 2020(2): 5-6. DOI: 10.3969/j.issn.1002-1701.2020.02.003.
[8]
Lewis KO, Popov V, Fatima SS. From static web to metaverse: reinventing medical education in the post-pandemic era[J]. Ann Med, 2024, 56(1): 2305694. DOI: 10.1080/07853890.2024.2305694.
[9]
Popov V, Mateju N, Jeske C, et al. Metaverse-based simulation: a scoping review of charting medical education over the last two decades in the lens of the 'marvelous medical education machine'[J]. Ann Med, 2024, 56(1): 2424450. DOI: 10.1080/07853890.2024.2424450.
[10]
Zaidi SSB, Adnan U, Lewis KO, et al. Metaverse-powered basic sciences medical education: bridging the gaps for lower middle-income countries[J]. Ann Med, 2024, 56(1): 2356637. DOI: 10.1080/07853890.2024.2356637.
[11]
Huang H, Yin J, Lv F, et al. A study on the impact of open source metaverse immersive teaching method on emergency skills training for medical undergraduate students[J]. BMC Med Educ, 2024, 24(1): 859. DOI: 10.1186/s12909-024-05862-9.
[12]
Einloft J, Meyer HL, Bedenbender S, et al. Immersive medical training: a comprehensive longitudinal study of extended reality in emergency scenarios for large student groups[J]. BMC Med Educ, 2024, 24(1): 978. DOI: 10.1186/s12909-024-05957-3.
[13]
Einloft J, Bedenbender S, Michelsen M, et al. Structured exposure achieves high acceptance of immersive technology among medical students and educators[J]. Cyberpsychol Behav Soc Netw, 2024, 27(6): 363-371. DOI: 10.1089/cyber.2023.0297.
[14]
Birrenbach T, Stuber R, Müller CE, et al. Virtual reality simulation to enhance advanced trauma life support trainings-a randomized controlled trial[J]. BMC Med Educ, 2024, 24(1): 666. DOI: 10.1186/s12909-024-05645-2.
[15]
Savir S, Khan AA, Yunus RA, et al. Virtual reality training for central venous catheter placement: an interventional feasibility study incorporating virtual reality into a standard training curriculum of novice trainees[J]. J Cardiothorac Vasc Anesth, 2024, 38(10): 2187-2197. DOI: 10.1053/j.jvca.2024.07.002.
[16]
Yee J, Holliday S, Spitzer CR, et al. Preparing interns for clinical practice through an institution-wide simulation-based mastery learning program for teaching central venous catheter placement[J]. Medicine, 2024, 103(23): e38346. DOI: 10.1097/MD.0000000000038346.
[17]
Bhugaonkar K, Bhugaonkar R, Masne N. The trend of metaverse and augmented & virtual reality extending to the healthcare system[J]. Cureus, 2022, 14(9): e29071. DOI: 10.7759/cureus.29071.
[18]
Wang Y, Zhu M, Chen X, et al. The application of metaverse in healthcare[J]. Front Public Health, 2024, 12: 1420367. DOI: 10.3389/fpubh.2024.1420367.
[19]
Ghaempanah F, Moasses Ghafari B, Hesami D, et al. Metaverse and its impact on medical education and health care system: a narrative review[J]. Health Sci Rep, 2024, 7(9): e70100. DOI: 10.1002/hsr2.70100.
[20]
郭辰樨, 欧凤荣. 虚拟现实技术在临床实践教学中的应用进展[J]. 沈阳医学院学报, 2021, 23(6): 513-516. DOI: 10.16753/j.cnki.1008-2344.2021.06.001.
[21]
刘革平, 王星, 高楠, 等. 从虚拟现实到元宇宙: 在线教育的新方向[J]. 现代远程教育研究, 2021, 33(6): 12-22.
[22]
华子荀, 黄慕雄. 教育元宇宙的教学场域架构、关键技术与实验研究[J]. 现代远程教育研究, 2021, 33(6): 23-31. DOI: 10.3969/j.issn.1009-5195.2021.06.003.
[23]
Triepels CPR, Smeets CFA, Notten KJB, et al. Does three-dimensional anatomy improve student understanding?[J]. Clin Anat, 2020, 33(1): 25-33. DOI: 10.1002/ca.23405.
[24]
Meyer-Szary J, Luis MS, Mikulski S, et al. The role of 3D printing in planning complex medical procedures and training of medical professionals-cross-sectional multispecialty review[J]. Int J Environ Res Public Health, 2022, 19(6): 3331. DOI: 10.3390/ijerph19063331.
[25]
马锦怡, 李鹏, 喻国艳, 等. 基于CT图像后处理技术人体骨关节系统三维图像在影像解剖学学习中的应用价值[J]. 海南医学, 2018, 29(14): 1991-1993. DOI: 10.3969/j.issn.1003-6350.2018.14.021.
[26]
Erolin C. Interactive 3D digital models for anatomy and medical education[J]. Adv Exp Med Biol, 2019, 1138: 1-16. DOI: 10.1007/978-3-030-14227-8_1.
[27]
Shi J, Fu S, Cavagnaro MJ, et al. 3D printing improve the effectiveness of fracture teaching and medical learning: a comprehensive scientometric assessment and future perspectives[J]. Front Physiol, 2021, 12: 726591. DOI: 10.3389/fphys.2021.726591.
[28]
朱佳伟, 潘周娴, 陈适, 等. 虚拟现实技术在医学领域的应用及展望[J]. 基础医学与临床, 2018, 38(3): 422-425. DOI: 10.16352/j.issn.1001-6325.2018.03.027.
[29]
Heinrich MA, Liu W, Jimenez A, et al. 3D bioprinting: from benches to translational applications[J]. Small, 2019, 15(23): e1805510. DOI: 10.1002/smll.201805510.
[30]
Matai I, Kaur G, Seyedsalehi A, et al. Progress in 3D bioprinting technology for tissue/organ regenerative engineering[J]. Biomaterials, 2020, 226: 119536. DOI: 10.1016/j.biomaterials.2019.119536.
[31]
甘淋玲, 沙川, 王博. VR技术在中国医学教学中的实践与思考[J]. 中华医学教育探索杂志, 2019, 18(9): 871-875. DOI: 10.3760/cma.j.issn.2095-1485.2019.09.002.
[1] 江瑶, 蒋程, 余翔, 谭莹, 温昕, 温慧莹, 彭桂艳, 李胜利. 基于注意力机制改进的子宫解剖结构检测与分割多任务模型的性能评估[J/OL]. 中华医学超声杂志(电子版), 2025, 22(08): 703-710.
[2] 陈明朗, 许凯, 黄稚熙, 梁博诚, 贺杰, 黄海珊, 马微波, 谭莹, 邹志英, 刘晓棠, 彭桂艳, 陈家希, 钟晓红. MobileNetV4:面向产前超声的主动脉弓分支异常智能诊断研究[J/OL]. 中华医学超声杂志(电子版), 2025, 22(08): 711-720.
[3] 杨丽仙, 黄稚熙, 梁博诚, 欧阳淑媛, 陈明朗, 赵英丽, 马薇波, 缪敬, 王磊, 袁鹰. 基于产前时序超声数据的新生儿出生体重智能预测[J/OL]. 中华医学超声杂志(电子版), 2025, 22(08): 721-732.
[4] 刘晴晴, 俞劲, 徐玮泽, 张志伟, 潘晓华, 舒强, 叶菁菁. OBICnet图像分类模型在小儿先天性心脏病超声筛查中的应用价值[J/OL]. 中华医学超声杂志(电子版), 2025, 22(08): 754-760.
[5] 傅小芳, 杨青翰, 孙昌琴, 豆梦杰, 胡峻溥, 孙灏, 吕发勤. 基于YOLO 11的肢体长骨骨折断端超声检测模型的临床价值[J/OL]. 中华医学超声杂志(电子版), 2025, 22(06): 541-546.
[6] 何冠南, 谭莹, 路玉欢, 蒲斌, 扬水华, 张仁铁, 陈明, 石智红, 钟晓红, 陈曦, 燕柳屹, 李胜利. 人工智能在胎儿超声心动图标准切面质量控制中的多中心应用研究[J/OL]. 中华医学超声杂志(电子版), 2025, 22(05): 388-396.
[7] 李宁, 王春丽, 路珊珊, 苏洁, 李纳. 智能盆底超声联合断层超声成像技术评估产后盆底功能障碍初产妇的临床研究[J/OL]. 中华妇幼临床医学杂志(电子版), 2025, 21(04): 475-481.
[8] 张家乐, 田璐, 伍国胜, 刘莹莹, 李志, 吴琼, 纪世召. 浅析人工智能在海战烧伤诊疗中的应用前景[J/OL]. 中华损伤与修复杂志(电子版), 2025, 20(05): 426-430.
[9] 石爽, 王艺, 史娜, 徐微. 多源信息融合下人工智能在慢性伤口管理中的精准应用与展望[J/OL]. 中华损伤与修复杂志(电子版), 2025, 20(05): 431-435.
[10] 郑仁杰, 张尊庶, 黄陈. 病理组学在胃癌诊治中的应用与挑战[J/OL]. 中华普通外科学文献(电子版), 2025, 19(04): 274-280.
[11] 左泽平, 宇洪涛, 朱金海, 钱俊杰, 徐秀民, 王一行, 梁朝朝, 郝宗耀. 智能无线腔镜在超微通道经皮肾镜取石术中的临床应用[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2025, 19(06): 736-741.
[12] 詹彧鸣, 张翔, 翁山耕. 人工智能在腹膜后肿瘤精准诊疗中的研究进展[J/OL]. 中华疝和腹壁外科杂志(电子版), 2025, 19(04): 371-376.
[13] 李媛媛, 李荣山. 机器学习:肾脏疾病研究与诊疗的新前沿[J/OL]. 中华肾病研究电子杂志, 2025, 14(04): 181-187.
[14] 王玲洁, 王瑷萍, 李朝军, 丁跃有, 杨德业, 赵清, 崔兆强, 王京昆, 王宏宇. 心脏和血管健康技术创新研发策略专家共识(2024第一次报告,上海)[J/OL]. 中华临床医师杂志(电子版), 2025, 19(05): 323-336.
[15] 刘霖, 张华华, 杨敏, 张茗茹, 妙银沙, 何子君, 赵哲, 吉金山, 王瑾, 韩继明. DeepSeek实践应用在急诊与灾难医学教学中的效果评价[J/OL]. 中华卫生应急电子杂志, 2025, 11(04): 238-243.
阅读次数
全文


摘要


AI


AI小编
你好!我是《中华医学电子期刊资源库》AI小编,有什么可以帮您的吗?