人工智能写作和大型语言模型技术在医疗保健文档:优势,局限性和建议
Sarah A Mess1,2,3, Alison J Mackey4, David E Yarowsky5
1From Sarah A. Mess, M. D., LLC, Columbia, MD.
人工智能 (AI) 书写工具通过使用大型语言模型 (LLM) 提供了医疗文档的效率. 然而,医生必须仔细校对人工智能生成的笔记,以发现潜在的错误和风险,如偏见和隐私问题.
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:
- 人工智能写字应用正在医疗保健中出现,用于医疗文档.
- 这些工具使用大型语言模型 (LLM) 和自动语音识别.
研究的目的:
- 评估与医疗保健中的AI写字应用相关的效率和风险.
- 强调医生监督在人工智能辅助医疗文档中的重要性.
主要方法:
- 人工智能书记者使用LLMs (例如,GPT-4) 处理医生与患者的互动.
- 自动语音识别捕获对话以生成医疗笔记和患者通信.
主要成果:
- 人工智能书记提供了快速的文档,增加了医生的认知自由.
- 人工智能产生的内容存在重大错误 (遗漏,伪造,替代) 的可能性.
- LLM可能会表现出不可预测的输出,缺乏医学知识限制,并构成隐私/偏见风险.
结论:
- 医生对人工智能生成的医疗笔记进行校对至关重要.
- 开发人员必须实施监管监督,道德准则和对医疗保健中人工智能的偏见纠正.
- 提高AI输出偏差的检测和纠正至关重要.
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