两个版本的人工智能系统的间隔乳腺癌检测诊断性能
Levent Çelik1, Davut Can Güner1, Ömer Özçağlayan1
1Department of Radiology, Maltepe University, School of Medicine, Istanbul, Turkey.
Acta radiologica (Stockholm, Sweden : 1987)
|September 18, 2023
概括
较新的Transpara v1.7人工智能工具在检测间隔乳腺癌 (IBC) 中的准确性比v1.6.6更高. 这种增强的AI性能可以帮助乳腺癌查计划.
科学领域:
- 医学成像和诊断 医学成像和诊断
- 医疗保健中的人工智能
- 在瘤学瘤学.
背景情况:
- 人工智能 (AI) 越来越多地被用作乳腺癌检测的诊断辅助.
- 间隔乳腺癌 (IBC) 仍然是乳腺查计划的一个重大挑战.
研究的目的:
- 为了比较两个版本的TransparaAI软件的诊断性能,v1.6和v1.7,用于检测间隔乳腺癌 (IBC).
主要方法:
- 对2,248,665张查性乳房造影的回顾性分析.
- 确定了323个IBC病例和441个对照.
- 使用Transpara v1.6和v1.7.7进行癌症风险评分 (1-10) 的评估.
- 通过接收器操作特征 (ROC) 曲线分析评估诊断性能.
主要成果:
- 与v1.6相比,Transpara v1.7表现出更高的灵敏度 (65.9%) 和特异性 (90%) (56.6%的灵敏度,90%的特异性).
- 曲线下的面积 (AUC) 在v1.7 (0.856) 显著高于v1.6 (0.812),表明诊断性能优越.
- 在7-12个月间隔检测期内,v1.7显示性能有所改善.
结论:
- 与v1.6.6相比,Transpara v1.7为识别间隔乳腺癌提供了增强的特异性,灵敏性和整体诊断性能.
- 像Transpara这样的AI系统可以在乳腺癌查计划中充当有价值的二级或三级读者.
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