人工智能CAD和放射科医生在查乳房镜中的错误解释的差异和相似之处
Mattie Salim1,2, Karin Dembrower1,3, Martin Eklund4
1Department of Oncology and Pathology, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden.
The British journal of radiology
|September 3, 2023
概括
人工智能 (AI) 和放射科医生在乳房影像解释错误中显示出差异. 将人工智能与放射科医生结合起来,可以提高老年妇女和乳腺密度较高的女性乳腺癌查准确度.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 乳房扫描查对于早期发现乳腺癌至关重要.
- 放射科医生的解释错误,包括错误的阳性和阴性,可能会影响查的有效性.
- 整合人工智能 (AI) 具有提高诊断准确性的潜力.
研究的目的:
- 为了比较人工智能和放射科医生在查乳房镜中的错误解释.
- 了解人工智能集成如何改变乳腺癌查中的诊断错误分布.
- 评估人工智能对虚假阳性和虚假阴性评估对患者人口统计学和瘤特征的影响.
主要方法:
- 从2008年至2015年进行的乳房扫描查数据的回顾性病例控制研究.
- 包括714名患有乳腺癌的妇女和8029名健康对照.
- 分析了AI,RAD 1和RAD 2在单个和双读者设置中的假阳性 (FP) 和假阴性 (FN) 评估,与年龄,密度,组织学和侵入性相关联.
主要成果:
- 在所有读者中,高密度和老年女性中,虚假负面评估的频率更高.
- 人工智能和放射学家在假阳性和假阴性率中展示了不同的模式.
- 在双读模拟中,人工智能集成显示出与双辐射学家读数相比,有可能减少假阳性评估.
结论:
- 人工智能显示出作为乳腺癌查中的补充工具的前景.
- 将人工智能与放射科医生相结合可能会增加灵敏度,特别是在高密度和老年女性中.
- 人工智能集成可能会改进乳房影像解释的准确性,改善查结果.
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