中华医学教育杂志

中华医学教育杂志 >

2026 , Vol. 46 >Issue 1: 8 - 14

DOI: https://doi.org/10.3760/cma.j.cn115259-20250930-01223

人工智能在医学教育中的应用

人工智能赋能人体形态学课程建设的路径、挑战与前景

  • 魏潇凡 ,
  • 吴江华 ,
  • 迟晓春 ,
  • 张卫光 ,
  • 彭宜红
展开
  • 1北京大学基础医学院人体解剖与组织胚胎学系,北京 100191;
    2北京大学基础医学院病理学系,北京 100191;
    3北京大学基础医学院病原生物学系,北京 100191
魏潇凡, Email: weixiaofan@bjmu.edu.cn

收稿日期: 2025-09-30

  网络出版日期: 2025-12-31

基金资助

北京大学医学部2025示范智慧课程建设专项(2025SFYB05); 北京大学2024本科生教学改革项目( JG2024132)

收起

Exploring the path, challenges, and prospects of artificial intelligence in empowering human morphology curriculum construction

  • Wei Xiaofan ,
  • Wu Jianghua ,
  • Chi Xiaochun ,
  • Zhang Weiguang ,
  • Peng Yihong
Expand
  • 1Department of Human Anatomy, Histology, and Embryology, School of Basic Medical Sciences, Peking University, Beijing 100191, China;
    2Department of Pathology, School of Basic Medical Sciences, Peking University, Beijing 100191, China;
    3Department of Pathogen Biology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
Wei Xiaofan, Email: weixiaofan@bjmu.edu.cn

Received date: 2025-09-30

  Online published: 2025-12-31

Supported by

Peking University Health Science Center 2025 Exemplary Smart Course Development Project(2025SFYB05); Peking University 2024 Undergraduate Teaching Reform Project(JG2024132)

Fold

摘要

人体形态学是医学教育的重要基础学科,其传统的形态结构及功能教学模式正面临数字化时代的多维挑战。本文立足医学教育智能化转型需求,系统探讨人工智能(artificial intelligence,AI)赋能人体形态学课程建设的实施路径,涵盖理论与实验教学。重点聚焦知识图谱驱动的AI智慧课程建设、AI识片系统开发、AI结合虚拟仿真实验等核心教学场景的创新应用,展望其潜在的前景。研究进一步深入剖析应用过程中可能存在的技术适配瓶颈与认知风险,智能技术与传统教学的协同机制等关键问题,并针对性提出合理的解决方案,为智能时代人体形态学教学的改革创新提供兼具前瞻性与实践性的策略参考。

关键词： 人工智能; 人体形态学; 医学教育; 课程建设

本文引用格式

魏潇凡 , 吴江华 , 迟晓春 , 张卫光 , 彭宜红 . 人工智能赋能人体形态学课程建设的路径、挑战与前景[J]. 中华医学教育杂志, 2026 , 46(1) : 8 -14 . DOI: 10.3760/cma.j.cn115259-20250930-01223

Abstract

As a fundamental discipline in medical education, human morphology faces multidimensional challenges in its traditional teaching models focusing on morphological structures and functional correlations during the digital era. Addressing the demand for intelligent transformation in medical education, this paper systematically explores the implementation pathways for empowering human morphology curriculum development with Artificial Intelligence (AI), encompassing both theoretical and laboratory instruction. It focuses on innovative applications in core teaching scenarios, including AI-powered smart course construction driven by knowledge graphs, the development of AI image recognition systems, and the integration of AI with virtual simulation experiments, while also envisioning their potential prospects. The research further conducts an in-depth analysis of critical issues such as technical adaptation bottlenecks, cognitive risks in practical applications, and synergistic mechanisms between intelligent technologies and conventional pedagogy. Targeted solutions are proposed to provide forward-looking and practical strategic insights for reforming human morphology education in the AI era.

Key words： Artificial intelligence; Human morphology; Medical education; Curriculum construction

参考文献

[1] 王富武,刘倩,刘尚明,等.医学形态学实验教学改革的探索与实践[J].基础医学教育,2022,24(6):409-411. DOI:10.13754/j.issn2095-1450.2022.06.08.
[2] 王维民. 第四代医学教育的深度剖析与实施策略[J].中华医学教育杂志, 2024, 44(10): 721-725. DOI:10.3760/cma.j.cn115259-20240722-00766.
[3] 信斯言, 沈子曰, 吴红斌. 面向未来医学教育 全球健康与人工智能: 2024AMEE年会综述2[J].中华医学教育杂志,2024,44(12): 896-900.DOI:10.3760/cma.j.cn115259-20241006-01031.
[4] Mintz Y, Brodie R. Introduction to artificial intelligence in medicine[J]. Minim Invasive Ther Allied Technol, 2019,28(2):73-81. DOI: 10.1080/13645706.2019.1575882.
[5] Gibney E. China's cheap, open AI model DeepSeek thrills scientists[J]. Nature, 2025,638(8049):13-14. DOI: 10.1038/d41586-025-00229-6.
[6] 常颜信, 钱尤雯. 人工智能在病理学教学中的应用[J].中国继续医学教育,2021,13(11):88-91. DOI:10.3969/j.issn.1674-9308.2021.11.024.
[7] 步宏. 积极推动人工智能在病理学的应用[J].中华病理学杂志,2021,50(4):307-309. DOI: 10.3760/cma.j.cn112151-20210219-00148.
[8] 姜华, 曲鹏. 线上教学平台在临床医学教学中的应用研究[J].中国继续医学教育,2021,13(20):77-81. DOI:10.3969/j.issn.1674-9308.2021.20.022.
[9] Ji S, Pan S, Cambria E, et al. A survey on knowledge graphs: representation, acquisition, and applications[J]. IEEE Trans Neural Netw Learn Syst, 2022,33(2):494-514. DOI: 10.1109/TNNLS.2021.3070843.
[10] 许智宏, 郝雪梅, 王利琴, 等. 多模态课程学习知识图谱实体预测方法研究[J].计算机科学与探索,2024,18(6):1590-1599. DOI:10.3778/j.issn.1673-9418.2308085.
[11] 我校首门课程知识图谱《组织学与胚胎学》上线智慧树网[EB/OL].(2024-04-22)[2025-09-30] .https://www.xjsmc.edu.cn/info/1024/2877.htm.
[12] 昆明医科大学首门课程知识图谱——病理学知识图谱上线运行[EB/OL].(2024-01-16)[2025-09-30] .https://www.kmmc.cn/mPages_2555_50353.aspx.
[13] 我校《系统解剖学》智慧课程上线, 打造医学人才培养新模式[EB/OL].(2024-07-05)[2025-09-30] . https://news.henu.edu.cn/info/1084/135477.htm.
[14] 即刻接入！MedSeek大模型全面开放, 面向医学院校及教学基地, 共启智慧教学新程[EB/OL].(2025-06-17)[2025-09-30] . https://medu.bjmu.edu.cn/cms/show.action?code=publish_4028801e6bf38f43016c2d3abc240370&siteid=100000&newsid=6ed55758ba044ba69e942b4a309e397e&channelid=0000000002.
[15] 杨会, 刘雪宇, 张兴娜, 等. 基于级联区域卷积神经网络算法在肾组织病理切片中对肾小球的识别与定位[J].第二军医大学学报,2021,42(4):445-450. DOI: 10.16781/j.0258-879x.2021.04.0445.
[16] Pan X, AbdulJabbar K, Coelho-Lima J, et al. The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma[J]. Nat Cancer, 2024,5(2):347-363. DOI: 10.1038/s43018-023-00694-w.
[17] 谢意, 周生源, 董彬, 等. 人工智能在胃癌图像组学研究中的应用进展[J].肿瘤综合治疗电子杂志,2025,11(1):1-9. DOI:10.12151/JMCM.2025.01-01.
[18] Lu MY, Chen B, Williamson D, et al. A visual-language foundation model for computational pathology[J]. Nat Med, 2024,30(3):863-874. DOI: 10.1038/s41591-024-02856-4.
[19] Chen RJ, Ding T, Lu MY, et al. Towards a general-purpose foundation model for computational pathology[J]. Nat Med, 2024,30(3):850-862. DOI: 10.1038/s41591-024-02857-3.
[20] Lu MY, Chen B, Williamson D, et al. A multimodal generative AI copilot for human pathology[J]. Nature, 2024,634(8033):466-473. DOI: 10.1038/s41586-024-07618-3.
[21] 尚宏伟, 路欣, 王稳, 等. 立足微观形态学实验教学的虚拟仿真实验建设[J].基础医学教育,2024,26(7):593-596. DOI: 10.13754/j.issn2095-1450.2024.07.12.
[22] 王绪明,桂华伟,钟新梅. HE染色虚拟仿真软件V1.0[Z].桂林医学院.2022.
[23] 宋超, 章文, 洪云霞, 等. 医学虚拟仿真教学的人工智能化前景探讨[J].医学教育研究与实践,2023,31(5):515-519. DOI: 10.13555/j.cnki.c.m.e.2023.05.001.
[24] 《中国智慧教育白皮书》发布 共同开启教育数字化发展新征程[EB/OL].(2025-05-17)[2025-09-30] . http://www.moe.gov.cn/jyb_xwfb/xw_zt/moe_357/2025/2025_zt06/dongtai/202505/t20250517_1190910.html.
[25] Totlis T, Natsis K, Filos D, et al. The potential role of ChatGPT and artificial intelligence in anatomy education: a conversation with ChatGPT[J]. Surg Radiol Anat, 2023,45(10):1321-1329. DOI: 10.1007/s00276-023-03229-1.
[26] Bajĉetić M, Mirĉić A, Rakoĉević J, et al. Comparing the performance of artificial intelligence learning models to medical students in solving histology and embryology multiple choice questions[J]. Ann Anat, 2024,254:152261. DOI: 10.1016/j.aanat.2024.152261.
Options
文章导航

/

〈 〉