生物医学大数据驱动的人工智能教学平台在医学教育改革实践中的应用

Application of biomedical big data-driven artificial intelligence teaching platform in medical education reform

摘要

生物医学大数据是推动精准医学、疾病预测预警以及医学教育创新的重要基础，将其与人工智能（AI）技术相融合将是构建医学生完整自适应培养体系的重要途径。研究开发AI赋能的“结构化文书生成－能力画像－知识问答－智能评分－决策生成”五大模块的有机整合教学平台，并纳入在安徽医科大学第二附属医院神经内科轮转的200名规培生进行培养，验证其应用效果。结果发现，观察组学生在感知易用性、有用性、学习投入度等维度评分均显著优于对照组；在决策生成模拟表现最优路径选择率及平均耗时、知识问答交互表现、应用准确率和响应速度等方面均较理想。研究表明，基于生物医学大数据的AI大模型赋能联动教学系统，可以为实现自适应医学教育提供新范式。

Abstract

Biomedical big data is an important foundation for advancing precision medicine, disease prediction and early warning, and innovation in medical education. The integration of biomedical big data with artificial intelligence (AI) technologies represents a pivotal approach to construct a comprehensive and adaptive training system for medical students. By developing an AI-empowered integrated teaching platform that integrates five core modules, including structured medical record automatic generation, competency profiling, knowledge-based question answering, intelligent assessment, and decision-making, this study enrolled and trained 200 students who rotated in the Department of Neurology at the Second Affiliated Hospital of Anhui Medical University, while evaluating the platform’s application efficacy. Results demonstrated that students in the observation group achieved significantly higher scores than those in the control group across dimensions such as perceived ease of use, perceived usefulness, and learning engagement. Additionally, the platform demonstrated ideal outcomes in terms of optimal path selection rate and average completion time in decision-making simulations, performance in knowledge-based interactive question answering, application accuracy, and response speed. This innovative teaching model enhanced students’ comprehensive clinical competencies, refined their diagnostic and therapeutic reasoning, and strengthened their ability to conduct standardized diagnosis and treatment. Concurrently, students developed a deeper understanding of the breadth and depth of medicine, ultimately achieving desirable educational outcomes. Therefore, the AI-empowered, large-model collaborative teaching system based on biomedical big data provides a new paradigm for delivering precise and adaptive medical education.

关键词

生物医学大数据 / 人工智能 / 实践教学 / 神经病学 / 多模态资料

Key words

biomedical big data / artificial intelligence / practical teaching / neurology / multimodal data

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基金资助

安徽省教育厅本科教育“四新”研究与改革实践项目“新医科背景下开展外科技能培训微专业的实践与探索研究”(2023sx200)

安徽省教育厅新时代育人省级质量工程项目（研究生教育）重点研究项目“‘新医科’背景下基于转化医学理念的外科学专业学位研究生教育与培养新模式探索”(2023jyjxggyjY087)

安徽省教育厅新时代育人省级质量工程项目（研究生教育）“外科学（普外）专业学位普通外科学教学案例库”(2023zyxwjxalk046)