人工智能支持的诊断辅助设备在识别正常胸部X射线图中的准确性:一项服务评估
Amrita Kumar1, Puja Patel1, Dennis Robert2
1Frimley Health NHS Foundation Trust, Frimley, United Kingdom.
BJR open
|October 1, 2024
概括
人工智能 (AI) 设备在识别正常的胸部X射线 (CXR) 中显示出高精度,负预测值为99.43%. 这证明了AI.
科学领域:
- 放射学和医学成像学 医学成像学
- 医疗保健中的人工智能
- 诊断的准确性 诊断的准确性
背景情况:
- 人工智能 (AI) 通过对正常和异常的胸部X射线 (CXR) 进行分类,有可能提高放射科医生的效率.
- 在现实世界的临床环境中评估人工智能工具的性能对于采用至关重要.
研究的目的:
- 评估AI设备 (qXR) 在识别正常胸部X射线 (CXRs) 中的准确性.
- 估计AI设备对正常CXRs的负预测值 (NPV).
主要方法:
- 从2022年11月到2023年1月,对522名全科医生和门诊患者的前部CXR进行了回顾性分析.
- 通过两位放射科医生的共识建立的基本真理.
- 计算AI性能指标,包括NPV,灵敏度,特异性和AUC.
主要成果:
- 对于正常的CXR,人工智能设备实现了高负预测值 (NPV) 的99.43%.
- 灵敏度为96.88%,特异性为75.55%,积极预测值为35.63%.
- 在ROC曲线下的面积 (AUC) 为91.92%,表明整体表现强.
结论:
- 人工智能设备在识别正常CXR方面表现出高精度,支持其潜在的实用性.
- 人工智能有可能优化放射科医生的工作流程并提高生产力.
- 需要进一步的证据来证实AI在CXR解释中的临床实用性和影响.
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