使用人工智能在胸部放射图上增加肺胸部检测的积极预测值的因素
Seungsoo Lee1, Eun-Kyung Kim1, Kyunghwa Han2
1Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, 363, Dongbaekjukjeon-Daero, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16995, South Korea.
Scientific reports
|August 23, 2024
概括
人工智能 (AI) 在胸部放射图上显示了41.1%的正预测值 (PPV) 来检测肺胸部. 像图像视图和并发的肺部疾病等因素显著影响AI.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医学成像分析 医学成像分析
背景情况:
- 人工智能 (AI) 越来越多地用于医学图像分析.
- 在胸部放射图 (CXR) 上检测肺胸部是关键的诊断任务.
- 评估AI在检测肺胸部的准确性是必不可少的.
研究的目的:
- 评估商业人工智能软件在CXR上识别肺胸部的积极预测值 (PPV).
- 确定影响基于AI的肺胸部检测PPV的因素.
主要方法:
- 从2021年3月到12月对87658个CXR进行了回顾性分析.
- 包括人工智能软件检测到肺胸部的情况.
- 放射科医生审查以确定真阳性 (TP) 和假阳性 (FP) 诊断.
- 后勤回归与通用估计方程来分析影响因素.
主要成果:
- 人工智能用于肺胸部检测的整体PPV为41.1% (136TP:195FP).
- 增加PPV的显著因素包括PA视图 (OR 29.8),高异常得分 (OR 1.08),大的肺胸体积 (OR 1.005),ipsilateral atelectasis (OR 3.5) 和小的ipsilateral 流 (OR 5.3).
结论:
- 人工智能用于肺胸部诊断的PPV是可变的.
- 诸如图像采集协议,患者特异性疾病和同时存在的胸部病变等因素影响AI性能.
- 人工智能算法和解释指南的进一步改进可能是必要的.
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