乳腺癌查中的读者偏见与癌症患病率和人工智能决策支持有关 - - 一项读者研究
Hanen Al-Bazzaz1, Marina Janicijevic1, Fredrik Strand2,3
1Mälarsjukhuset Eskilstuna, Kungsvägen 42, 633 49, Eskilstuna, Sweden.
European radiology
|January 2, 2024
概括
乳房镜查中的高癌症患病率增加了放射科医生的灵敏度,但降低了特异性. 人工智能 (AI) 决策支持进一步调整了这些指标,突出了需要仔细监测后实施的必要性.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 医疗保健中的人工智能
背景情况:
- 查性乳房造影对于早期发现乳腺癌至关重要.
- 放射科医生的表现可能会受到病例组合的影响,例如癌症患病率.
- 人工智能 (AI) 越来越多地用于医疗成像中的决策支持.
研究的目的:
- 评估高癌症患病率对乳腺放射科医生的表现的影响.
- 评估人工智能决策支持对放射科医生的敏感性和乳房图解特异性的影响.
主要方法:
- 2010-2013年使用查性乳房造影的读者研究,癌症与健康的比例为1:1.
- 放射科医生首先在没有人工智能的情况下解释了乳房影像,然后使用人工智能决策支持.
- 使用千二测试进行的统计分析与性能指标进行了比较.
主要成果:
- 在高癌症患病率的环境中,与原始查相比,放射科医生的灵敏度增加到81%,特异性降低到67%.
- 人工智能决策支持进一步转移了性能,灵敏度为75%,特异性为86%.
- 人工智能的影响在读者之间有所不同,并取决于图像特征.
结论:
- 高癌症患病率显著改变了放射科医生的表现,增加了灵敏度和降低了特异性.
- 人工智能决策支持将放射科医生的表现与人工智能自身的灵敏度和特异性进行校准.
- 对选指标的实施后监测对于确保人工智能集成后的期望结果至关重要.
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