黑盒子警告:大型语言模型和传染病的未来 咨询咨询
Ilan S Schwartz1, Katherine E Link2,3, Roxana Daneshjou4,5
1Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
概括
大型语言模型 (LLM) 在医学上表现有前途,但存在诸如说法和偏见等局限性,防止安全的临床使用. 传染病临床医生必须与LLM接触,以指导他们负责任地融入专业护理.
科学领域:
- 人工智能在医学中的应用
- 医疗信息学 医疗信息学
- 临床决策支持 临床决策支持
背景情况:
- 大型语言模型 (LLM) 展示了接近医生在医疗任务上的表现的能力.
- 支持者建议LLMs进行临床咨询,引发人们对认知专业的未来的担忧.
- 目前的LLM限制阻碍了在专家咨询中安全的临床部署.
研究的目的:
- 批判性地评估临床应用LLM的当前能力和局限性.
- 倡导传染病临床医生与LLM技术的知情参与.
- 引导LLMs在增强专业医疗保健中的负责任整合.
主要方法:
- 在医疗挑战中LLM绩效的分析.
- 识别关键的局限性,包括共,缺乏上下文意识和偏见.
- 评估快速进步和对LLMs临床整合的要求日益增加.
主要成果:
- LLM经常表现出口,缺乏诊断和治疗的关键上下文意识.
- 法学士培训数据和方法往往是难以辨认的,它们可以使偏见永久化.
- 尽管存在局限性,但LLM正在迅速改善,需要积极参与.
结论:
- 在专家咨询中,LLM还不适合安全的临床部署.
- 传染病临床医生必须积极参与LLM,以塑造其适当的使用.
- 有信息的宣传至关重要,以确保LLM增强而不是破坏专业护理.
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