在精神病学中,人工智能辅助生成病例情景和多选题:试点研究
Emre Emekli1, Esra Emekli2, Beren Özel3
1Faculty of Medicine, Eskişehir Osmangazi University, Eskişehir, Turkey. emreemekli90@gmail.com.
概括
聊天GPT-4可以创建相关的精神病学案例研究和多选题 (MCQs) 用于教育. 专家审查对于细化问题和确保评估临床推理的清晰度至关重要.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 精神病学培训 精神病学培训
背景情况:
- 本科精神病学教育依赖于基于案例的学习.
- 开发高质量的多选题 (MCQ) 是耗时的.
- 像ChatGPT-4这样的大型语言模型 (LLM) 显示了教育内容生成的潜力.
研究的目的:
- 评估ChatGPT-4在为精神病学生成基于病例的MCQ的能力.
- 评估人工智能生成的教育材料的质量和临床相关性.
- 为了确定人工智能产生的问题是否评估临床推理与默认知识.
主要方法:
- 聊天GPT-4在12个精神病诊断中产生了12个临床细节和60个MCQ.
- 精神病学家评估了生成的图片,MCQ和答案选项.
- 评估的重点是项目难度,干扰因子的可信性,临床相关性和临床推理的评估.
主要成果:
- 大多数产生的项目 (71%) 具有适当的难度,而72%的分心因素是可信的.
- 临床图片在代表性和相关性方面获得了很高的评分.
- 大多数评估者 (21/24) 证实了评估临床推理的问题,而不仅仅是背诵知识.
结论:
- 聊天GPT-4显示了产生临床相关精神病学教育内容的希望.
- 人工智能生成的MCQ可以支持本科精神病学中的基于案例的学习.
- 专家监督对于改进人工智能产生的问题至关重要,特别是对于临床判断和减少模两可.
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