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Can AI serve as an independent second reader of mammograms? A simulation study

机译:AI可以作为乳房X线照片的独立第二读者吗?模拟研究

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In this study we used a large previously built database of 2,892 mammograms and 31,650 single mammogram radiologists' assessments to simulate the impact of replacing one radiologist by an AI system in a double reading setting. The double human reading scenario and the double hybrid reading scenario (second reader replaced by an AI system) were simulated via bootstrapping using different combinations of mammograms and radiologists from the database. The main outcomes of each scenario were sensitivity, specificity and workload (number of necessary readings). The results showed that when using AI as a second reader, workload can be reduced by 44%, sensitivity remains similar (difference -0.1%; 95% CI = -4.1%, 3.9%), and specificity increases by 5.3% (P<0.001). Our results suggest that using AI as a second reader in a double reading setting as in screening programs could be a strategy to reduce workload and false positive recalls without affecting sensitivity.
机译:在这项研究中,我们使用了一个大型的先前建立的数据库,该数据库包含2,892幅X线照片和31,650幅单张X线照片的放射线医师的评估,以模拟在双重阅读设置中用AI系统替代一名放射线医师的影响。使用乳房X线照片和放射线医师的不同组合,通过自举法模拟了双重人类阅读场景和双重混合阅读场景(第二阅读器被AI系统取代)。每种情况的主要结果是敏感性,特异性和工作量(必要的读数数量)。结果表明,使用AI作为第二阅读器时,工作量可以减少44%,灵敏度保持相似(差异-0.1%; 95%CI = -4.1%,3.9%),特异性提高5.3%(P < 0.001)。我们的结果表明,在筛查程序中,在复读环境中使用AI作为第二阅读器可能是一种在不影响敏感性的情况下减少工作量和误报率的策略。

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