Development and application of an artificial intelligence-assisted learning platform for the entire process of medical education

Chen Yuanshuai; Jiang Luhua; Ding Yigang; Shen Sisi; Shen Jing

doi:10.3760/cma.j.cn116021-20251012-02332

您当前的位置：

首页 >

文章列表页 >

Development and application of an artificial intelligence-assisted learning platform for the entire process of medical education

更新时间：2026-07-31

- Development and application of an artificial intelligence-assisted learning platform for the entire process of medical education
- Chinese Journal of Medical Education Research Pages: 1-8(2026)
- 作者机构：
  
  1.浙江大学医学院附属第二医院人工智能与信息化部，杭州 310009
  2.浙江大学医学院医学教育研究中心，杭州 310058
  3.浙江大学医学院本科生教育办公室，杭州 310058
- 作者简介：
  
  Shen Jing, Email: shenjingwzy@zju.edu.cn
- 基金信息：
  
  Key Project of Higher Education Research of Zhejiang Higher Education Association in 2025(KT2025001);Key Project of the 2024 Higher Education Science Research Plan of the Chinese Society of Higher Education(24BJ0311);2025 Medical Education Research Project of the Medical Education Branch of the Chinese Medical Association and the National Medical Education Development Center(2025B349)
- DOI：10.3760/cma.j.cn116021-20251012-02332
  CLC： R-0;R-4
- Received：12 October 2025，
  
  Online First：31 July 2026，
- 稿件说明：
移动端阅览
Chen Yuanshuai, Jiang Luhua, Ding Yigang, et al. Development and application of an artificial intelligence-assisted learning platform for the entire process of medical education[J/OL]. Chinese Journal of Medical Education Research, 2026, 1-8.
DOI：

Chen Yuanshuai, Jiang Luhua, Ding Yigang, et al. Development and application of an artificial intelligence-assisted learning platform for the entire process of medical education[J/OL]. Chinese Journal of Medical Education Research, 2026, 1-8. DOI： 10.3760/cma.j.cn116021-20251012-02332.

摘要

目的

构建并应用一个覆盖医学教育“学、教、考、评”全流程的人工智能助学平台，提升个性化学习支持与过程性评价能力。

方法

以启真医学大模型为知识与推理底座，建设“启真智医”AI助学平台。该平台包括自主学习、学习活动、考核评价与教学质量监控四个功能模块，构建多场景智能体，面向教师端、学生端与督导端协同运行，形成数据驱动的教学闭环。

结果

讨论课智能体已覆盖28间PBL讨论室，完成150次教学分析。考核评价模块已支持32场考试，累计考评2 505人次，并与教学质量监控模块联动输出课程与个体改进建议。

结论

该平台通过“医学教育专属大模型+多智能体协同”实现一体化智能支撑与可量化的过程性评价，为第四代医学教育提供可落地、可复用的数字助学范式。

Abstract

Objective

To develop and implement an artificial intelligence (AI)-assisted learning platform covering the entire process of "learning

teaching

assessment

and evaluation" in medical education

and to enhance personalized learning support and formative evaluation capabilities.

Methods

Using the Qizhen Medical Large Model as the knowledge and reasoning foundation

the "Qizhen MedInspire" AI-assisted learning platform was constructed. The platform consisted of four functional modules: self-directed learning

learning activities

assessment and evaluation

and teaching quality monitoring. Multiple scenario-based intelligent agents were developed to operate collaboratively across teacher

student

and supervisor interfaces

forming a data-driven closed-loop teaching system.

Results

The discussion-class agent was deployed in 28 PBL rooms and completed 150 instructional analyses. The assessment module supported 32 examinations

involving a total of 2 505 assessment instances

and worked in conjunction with the teaching quality monitoring module to generate course-level and individual improvement recommendations.

Conclusions

By integrating a "medical education-specific large model + multi-agent collaboration" approach

the platform provides comprehensive intelligent support and quantifiable formative evaluation. It offers a practical and replicable digital learning-support paradigm for fourth-generation medical education.

关键词

Keywords

references

关庆，陆萍，韩旭，等 . 生成式人工智能赋能医学免疫学教学实践研究 [J ] . 中国免疫学杂志， 2025 ， 41 （ 6 ）： 1306 - 1309， 1314 . DOI: 10.3969/j.issn.1000-484X.2025.06.006 http://dx.doi.org/10.3969/j.issn.1000-484X.2025.06.006 .

王涛，王渊，胡浩 . 人工智能赋能医学基础实验教学的挑战与思考 [J ] . 中国医学教育技术， 2025 （ 5 ）： 563 - 567 .

陈泞夙，赵凯，薛心雨，等 . 基于人工智能的临床辅助决策系统早期临床评价研究的报告规范（DECIDE-AI）解读 [J ] . 中国循证医学杂志， 2024 ， 24 （ 9 ）： 1100 - 1107 .

吴敏敏，王鑫钰，王伟炳 . 医学人工智能的技术发展和场景应用 [J ] . 复旦学报（医学版）， 2025 ， 52 （ 3 ）： 470 - 474 . DOI: 10.3969/j.issn.1672-8467.2025.03.021 http://dx.doi.org/10.3969/j.issn.1672-8467.2025.03.021 .

李秀岩，冯冬菲，王艳宏，等 . 世界四大传统医学教育体系及对中医药教育的启示 [J ] . 中国医院管理， 2024 ， 44 （ 8 ）： 84 - 88 .

王艳霞，胡优敏，倪雯雯，等 . 基于国家级虚拟仿真一流课程的实验PBL教学模式构建与实践 [J ] . 中华医学教育探索杂志， 2025 ， 24 （ 3 ）： 325 - 330 . DOI: 10.3760/cma.j.cn116021-20230620-01860 http://dx.doi.org/10.3760/cma.j.cn116021-20230620-01860 .

Frenk J , Chen L , Bhutta ZA , et al . Health professionals for a new century: transforming education to strengthen health systems in an interdependent world [J ] . Lancet , 2010 , 376 ( 9756 ): 1923 - 1958 . DOI: 10.1016/S0140-6736(10)61854-5 http://dx.doi.org/10.1016/S0140-6736(10)61854-5 .

韩玉，徐涵，赵楚 . 职业教育专业能力标准的数智化：能力图谱及应用场景开发 [J ] . 教育研究与实验， 2024 （ 5 ）： 99 - 107 .

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 http://dx.doi.org/10.3760/cma.j.cn115259-20240722-00766 .

中国住院医师培训精英教学医院联盟 . 中国住院医师培训精英教学医院联盟住院医师核心胜任力框架共识 [J ] . 协和医学杂志， 2022 ， 13 （ 1 ）： 17 - 23 . DOI: 10.12290/xhyxzz.2021-0755 http://dx.doi.org/10.12290/xhyxzz.2021-0755 .

李永智，安德烈亚斯·施莱歇尔 . 人工智能时代的能力重构与教育变革：全球趋势探析 [J ] . 全球教育展望， 2025 ， 54 （ 9 ）： 3 - 19 .

厉旭云 , 孙岑岑 , 齐宏妍 , 等 . 四融支撑、四维一体医学生理学实验教学模式重构与实践 [J ] . 基础医学教育， 2025 ， 27 （ 11 ）： 1028 - 1031 . DOI: 10.13754/j.issn2095-1450.2025.11.04 http://dx.doi.org/10.13754/j.issn2095-1450.2025.11.04 .

朱平，姜晓蓉，许宇珩，等 . 新医科，正在培育怎样的医学生 [N ] . 浙江日报， 2025-10-15 .

孙江山 . 基于3D CAD的中学生空间能力提升：模型构建与课堂实践 [J ] . 中国电化教育， 2022 （ 9 ）： 114 - 121 .

徐建鑫 . 基于Docker的网络安全靶场设计与实现 [J ] . 网络安全和信息化， 2025 （ 5 ）： 98 - 100 .

Niu X . Deep-learning-guided student intelligent classroom management system [J ] . Appl Bionics Biomech , 2022 , 2022 : 1961631 . DOI: 10.1155/2022/1961631 http://dx.doi.org/10.1155/2022/1961631 .

田蕾，孙宝志 . 第四代医学教育考核评价：精准教育评价 [J ] . 中华医学教育探索杂志， 2025 ， 24 （ 11 ）： 1441 - 1446 . DOI: 10.3760/cma.j.cn116021-20250401-02127 http://dx.doi.org/10.3760/cma.j.cn116021-20250401-02127 .

朱渝珊，张文，王晓珂，等 . 面向电子商务社交知识图谱高效增量预训练的双向模仿蒸馏 [J ] . 软件学报， 2025 ， 36 （ 3 ）： 1218 - 1239 .

王欣宇，杨涛，王松，等 . 融合监督微调和检索增强的中医知识问答模型研究 [J ] . 世界科学技术-中医药现代化， 2025 ， 27 （ 7 ）： 1898 - 1905 . DOI: 10.3321/j.issn:1673-8225.2007.35.013 http://dx.doi.org/10.3321/j.issn:1673-8225.2007.35.013 .

Haider Z , Rahman MH , Devabhaktuni V , et al . A framework for mitigating malicious RLHF feedback in LLM training using consensus based reward [J ] . Sci Rep , 2025 , 15 : 9177 . DOI: 10.1038/s41598-025-92889-7 http://dx.doi.org/10.1038/s41598-025-92889-7 .

Chang E , Sung S . Use of SNOMED CT in large language models: scoping review [J ] . JMIR Med Inform , 2024 , 12 : e62924 . DOI: 10.2196/62924 http://dx.doi.org/10.2196/62924 .

Kim S , Yang H , Kim Y , et al . Hydra : Multi-head low-rank adaptation for parameter efficient fine-tuning [J ] . Neural Netw , 2024 , 178 : 106414 . DOI: 10.1016/j.neunet.2024.106414 http://dx.doi.org/10.1016/j.neunet.2024.106414 .

曹来成，后杨宁，冯涛，等 . 面向动态博弈的k-匿名隐私保护数据共享方案 [J ] . 西安电子科技大学学报（自然科学版）， 2024 ， 51 （ 4 ）： 170 - 179 . DOI: 10.19665/j.issn1001-2400.20240201 http://dx.doi.org/10.19665/j.issn1001-2400.20240201 .

Yuan J , Zhou F , Guo Z , et al . HCformer: hybrid CNN-transformer for LDCT image denoising [J ] . J Digit Imaging , 2023 , 36 ( 5 ): 2290 - 2305 . DOI: 10.1007/s10278-023-00842-9 http://dx.doi.org/10.1007/s10278-023-00842-9 .

Misera L , Müller-Franzes G , Truhn D , et al . Weakly supervised deep learning in radiology [J ] . Radiology , 2024 , 312 : e232085 . DOI: 10.1148/radiol.232085 http://dx.doi.org/10.1148/radiol.232085 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Promoting deep integration of artificial intelligence and education for new pathways of precision learning

Application and prospect of large language model in the education of public health and preventive medicine in colleges and universities

A survey on the current use and ethical awareness of artificial intelligence among medical trainees

Research progress and prospects of artificial intelligence in new models of clinical reasoning education

Trends in learning gains of intern nurses in obstetrics and gynecology and their correlations with learning beliefs and academic emotions

Related Author

Qu Bo

Zhang Xixiaoxue

Wang Xuechun

Liu Liangying

Wu Wenjun

Ma Yu

Yan Hongda

He Yao

Related Institution

China Medical University

General Affairs Office, Graduate School of Chinese PLA General Hospital

Graduate School of Chinese PLA General Hospital

Library of Graduate School of Chinese PLA General Hospital

National Clinical Research Center for Geriatric Diseases, Second Medical Center, Chinese PLA General Hospital

⁰