使用ChatGPT-4从医生与患者接触的音频录音中创建结构化的医疗笔记:比较研究
Annessa Kernberg1, Jeffrey A Gold1, Vishnu Mohan1
1Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Sciences University, Portland, OR, United States.
聊天GPT-4生成具有重大错误,主要是遗漏和可变质量的临床笔记. 它的准确性随着更长的成绩单而下降,使其不适合当前的临床文档.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 准确的医疗文件对于患者的护理和沟通至关重要.
- 不准确性和文档负担导致医生倦怠.
- 目前用于文档的AI解决方案在准确性和工作流集成方面存在局限性.
研究的目的:
- 评估ChatGPT-4产生的主观,目标,评估和计划 (SOAP) 笔记的准确性和质量.
- 将人工智能生成的笔记与患者接触的黄金标准成绩单进行比较.
- 识别和分类人工智能生成的医疗文档中的错误.
主要方法:
- 模拟的患者与医疗服务提供者的接触被转录.
- 从这些成绩单中,ChatGPT-4生成了SOAP笔记.
- 笔记与黄金标准进行了比较,对错误进行了分类 (遗漏,添加,不正确信息),并使用医生文档质量仪器 (PDQI) 评估质量.
主要成果:
- 聊天GPT-4平均每案产生23.6个错误,其中86%是遗漏.
- 笔记准确性在复制品之间有显著差异 (52.9%对所有3个都准确).
- 准确性与转录长度和数据复杂性相反相关.
结论:
- 聊天GPT-4在错误率,准确性和笔记质量方面表现出相当大的变化.
- 模型的性能受到转录长度和数据复杂性的影响.
- 目前人工智能生成的笔记不符合临床标准,在广泛采用之前需要谨慎.
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