在医学AI查询中寻找完美的提示符
Florian Berghea1, Elena Camelia Berghea2, Cristina Octaviana Daia1,2
1Sfanta Maria Clinical Hospital, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Frontiers in artificial intelligence
|December 3, 2025
概括
快速质量显著影响医疗人工智能 (AI) 的性能,影响准确性和可靠性. 优化提示对于在医疗保健中安全公平地部署人工智能至关重要.
科学领域:
- 医疗人工智能 医疗人工智能
- 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:
- 医疗人工智能 (AI) 系统的评估是具有挑战性的,因为研究中的性能可变性.
- 快速质量,或如何向AI提出问题,是影响AI结果的未被认可的因素.
- 现有的文献显示了人工智能表现的不一致性,从超越人类专家到在更广泛的分析中表现不佳.
研究的目的:
- 调查快速工程对医学对话AI感知的准确性和可靠性的影响.
- 确定快速质量的关键作用在医疗AI的性能悖论中.
- 探索专家制定的提示和公众查询之间的差距,解决安全和健康公平问题.
主要方法:
- 科学文献的叙述性审查.
- 分析重点关注2018年1月至2025年8月的出版物.
- 调查提示特征和AI性能指标之间的关系.
主要成果:
- 一个"性能悖论"存在于人工智能在受控设置中脱而出,但在现实世界的应用中陷入困境,与提示类型密切相关.
- 促使偏见可以使研究结论无效,人工智能幻觉可能会产生错误的医疗信息.
- 在专家级提示和自然公众查询之间发现了显著的差异,影响了AI的实际实用性和安全性.
结论:
- 提示工程是医疗AI可靠性和准确性的关键决定因素.
- 解决提示偏见和人工智能幻觉对于值得信赖的医疗人工智能至关重要.
- 弥合专家和公众提示之间的差距对于安全,公平和有效的AI整合到医疗保健中至关重要.
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