诊断范围:人工智能看不到头脑不知道的东西
Gary E Weissman1,2,3,4, Laura Zwaan5, Sigall K Bell6
114640 Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA, USA.
Diagnosis (Berlin, Germany)
|December 3, 2024
概括
了解诊断范围对于开发有效的人工智能 (AI) 诊断工具至关重要. 精确测量这一范围可以确保人工智能系统与临床需求保持一致,促进诊断卓越和患者安全.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 临床决策支持 临床决策支持
背景情况:
- 诊断范围,临床环境中的诊断范围,对于人工智能培训至关重要.
- 它对人工智能系统和诊断过程的影响目前尚未得到充分探索.
研究的目的:
- 定义诊断范围及其在基于AI的诊断决策支持系统中的作用.
- 审查测量和使用诊断范围的挑战.
- 识别未来研究的知识差距.
主要方法:
- 诊断范围的概念定义.
- 讨论它在人工智能开发中的作用.
- 审查现有文献和挑战.
主要成果:
- 诊断范围不同于差异诊断,因临床环境,人口和资源而异.
- 真实,观察和考虑范围之间的分歧为AI带来了挑战和机遇.
- 定制人工智能工具需要为特定设置指定和测量诊断范围.
结论:
- 当人工智能工具与患者/临床医生的需求保持一致,并接受准确诊断范围的培训时,它可以提高诊断的卓越性.
- 了解和评估诊断范围是诊断中最佳的人类-AI合作的关键.
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