The application, challenges, and prospects of large language models in pediatric clinical medical education

Yang Zhangya; Lü Kuilin; Wang Hongqian; Wang Qi; Zhang Yuping; Yang Wang; Tang Xuemei; Wu Zhifeng

doi:10.3760/cma.j.cn116021-20250811-02342

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The application, challenges, and prospects of large language models in pediatric clinical medical education

更新时间：2026-07-31

- The application, challenges, and prospects of large language models in pediatric clinical medical education
- Chinese Journal of Medical Education Research Pages: 1-6(2026)
- 作者机构：
  
  1.陆军军医大学第二附属医院儿科，重庆 400037
  2.陆军军医大学第一附属医院人工智能与大数据中心，重庆 400038
  3.陆军军医大学第二附属医院医务处，重庆 400037
  4.重庆医科大学儿科学院内科教研室，重庆 400014
- 作者简介：
  
  Wu Zhifeng, Email: wuzhifeng@tmmu.edu.cn
- 基金信息：
  
  Chongqing Higher Education Teaching Reform Research Project Digitalization Project(244136);Chongqing Municipal Education Commission Science and Technology Research Program Project(KJQN202512808);Cultivation of Teaching Achievements, Digital Teaching Reform Project of Army Medical University
- DOI：10.3760/cma.j.cn116021-20250811-02342
  CLC： R-05
- Received：11 August 2025，
  
  Online First：31 July 2026，
- 稿件说明：
移动端阅览
Yang Zhangya, Lü Kuilin, Wang Hongqian, et al. The application, challenges, and prospects of large language models in pediatric clinical medical education[J/OL]. Chinese Journal of Medical Education Research, 2026, 1-6.
DOI：

Yang Zhangya, Lü Kuilin, Wang Hongqian, et al. The application, challenges, and prospects of large language models in pediatric clinical medical education[J/OL]. Chinese Journal of Medical Education Research, 2026, 1-6. DOI： 10.3760/cma.j.cn116021-20250811-02342.

摘要

儿科临床医学教育是培养高素质儿科专业人才的核心环节，当前面临教学场景不足、婴幼儿症状表述缺失导致的诊疗链条断裂、有创操作训练伦理受限、医患沟通情境模拟困难等突出问题。本文聚焦大语言模型在该领域的应用价值，通过整合多模态数据构建动态病例库、结合虚拟仿真系统革新操作训练、设计情景化平台优化医患沟通，建立病种知识库、形成相关智能体和模拟真实临床场景，为儿科临床教学提供了创新解决方案。本文系统探讨大语言模型在儿科临床医学教育中的应用场景、核心挑战及未来优化方向，提出“数据-伦理-技术”三位一体发展框架，为技术落地与教育模式创新提供理论与实践参考。

Abstract

Pediatric clinical medical education is central to cultivating high-quality pediatric professionals. However

it faces significant challenges

including insufficient teaching scenarios

breakdowns in the diagnostic chain due to the inability of infants and toddlers to describe symptoms

ethical constraints on invasive procedure training

and difficulties in simulating doctor–patient communication. This article explores the application value of large language models in addressing these issues. By integrating multimodal data to construct dynamic case libraries

innovating procedural training through virtual simulation systems

and designing contextual platforms to enhance doctor-patient communication

we developed disease knowledge bases

intelligent agents

and realistic clinical scenario simulations. These advances provide innovative solutions for pediatric clinical education. This paper systematically examined the application scenarios

core challenges

and future optimization directions for large language models in this field

and proposed a "data

ethics

technology" trinity development framework. This study provides both a theoretical and a practical reference for technology implementation and educational model innovation.

关键词

Keywords

references

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