评估ChatGPT作为医学学习者和临床医生的诊断工具
Ali Hadi1, Edward Tran1, Branavan Nagarajan1
1Department of Paediatrics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
PloS one
|July 31, 2024
概括
聊天GPT的诊断准确性有限,仅在49%的医疗病例中正确回答. 然而,它显示出作为医疗学员的教育工具的潜力,简化复杂的概念并帮助差异诊断.
科学领域:
- 人工智能在医学中的应用
- 医疗教育 技术 技术 医学教育
- 自然语言处理应用程序
背景情况:
- 一个大型语言模型 (LLM) ChatGPT 在广泛的文本数据上受过训练,因此具有作为诊断辅助和教育资源的潜力.
- 它理解和生成人类语言的能力,为医疗学员的互动提供了便利.
- 这项研究评估了ChatGPT的诊断准确性及其在医学教育中的实用性.
研究的目的:
- 通过医学案例挑战来调查ChatGPT的诊断准确性.
- 评估ChatGPT作为医学学员教育工具的实用性.
- 分析ChatGPT提供的医疗信息质量,认知负载和响应相关性.
主要方法:
- 150个Medscape案例挑战 (2021年9月至2023年1月) 被输入到ChatGPT.
- 主要结果:正确答案案的百分比.
- 二次结果:诊断准确度指标 (精度,灵敏度,特异性,AUC),认知负载和响应的定性内容分析.
主要成果:
- 在49% (74/150) 的案例中,ChatGPT正确地回答了问题.
- 整体诊断准确率为74%,精度为48.67%和灵敏度为48.67%.
- 大多数响应的认知负载较低 (51%),被认为是完整和相关的 (52%).
结论:
- 目前,ChatGPT的准确性还不足以作为一个独立的诊断工具.
- 虽然它难以解释复杂的数据,如实验室值和成像,但它通过简化概念和建议差异诊断来提供教育价值.
- 未来的研究应该专注于利用ChatGPT在医学教育中的优势,特别是解释复杂主题和指导诊断推理.
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