放射学中的人工智能:机遇和挑战
Marta N Flory1, Sandy Napel1, Emily B Tsai1
1Department of Radiology, Stanford University School of Medicine, Center for Academic Medicine, Palo Alto, CA.
Seminars in ultrasound, CT, and MR
|February 25, 2024
概括
人工智能 (AI) 提供了放射学方面的进步,但由于有偏见的数据,它存在风险. 放射科医生必须与开发人员合作,以确保负责任的AI实施,并减轻潜在的危害.
科学领域:
- 医学成像信息学 医学成像信息学
- 人工智能的临床应用 人工智能的临床应用
背景情况:
- 人工智能 (AI) 在放射学中的整合为改善临床实践,教育和研究提供了重大机会.
- 然而,当前的AI系统是针对特定数据集进行训练的,这些数据集可能存在固有的偏见和不准确性.
研究的目的:
- 突出AI在放射学中的双重性质,包括其潜在的好处和固有的风险.
- 强调放射科医生在AI开发生命周期中的关键作用.
主要方法:
- 对放射学中人工智能的当前文献的综述.
- 分析AI算法的潜在偏见和局限性.
- 讨论放射科医生和人工智能开发人员之间的合作过程.
主要成果:
- 人工智能承诺通过提高效率和诊断能力来彻底改变放射学.
- 有关数据偏差,算法透明度和诊断错误的可能性存在重大担忧.
- 放射科医生的积极参与对于道德AI开发和部署至关重要.
结论:
- 放射科医生必须对人工智能的局限性有充分的了解,包括数据偏差和不准确性.
- 在整个过程中,从概念到实施,与人工智能开发人员积极参与是必不可少的.
- 协作努力是最大限度地发挥人工智能的好处的关键,同时最大限度地减少放射学实践中的潜在危害.
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