基于人工智能的肺结核计算机辅助检测 (AI-CAD) 适用于基于社区的活跃病例发现
Kosuke Okada1,2, Norio Yamada3, Kiyoko Takayanagi4
1The Research Institute of Tuberculosis (RIT), Japan Anti-Tuberculosis Association (JATA), Tokyo, Japan. okadak@jata.or.jp.
Tropical medicine and health
|January 1, 2024
概括
基于人工智能的计算机辅助检测 (AI-CAD) 在社区环境中显示出结核病查的前景. 这种人工智能工具可以显著减少对人类读者和实验室工作的需求,以积极寻找案例.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 公共卫生 公共卫生
背景情况:
- AI-CAD用于结核病 (TB) 检测的商业可用性.
- 关于AI-CAD在基于社区的积极案例寻找 (ACF) 中的表现的有限数据.
研究的目的:
- 评估AI-CAD在柬埔寨社区结核病ACF中的适用性和性能.
- 评估AI-CAD对人类读者和实验室服务工作量减少的影响.
主要方法:
- 分析来自柬埔寨社区ACF的匿名数据.
- 胸部放射 (CXR) 查,然后对符合条件的参与者进行Xpert测试.
- 经验丰富的医生和AI-CAD对CXR的回顾性解释,并进行ROC分析以评估性能.
主要成果:
- 在CXR上,AI-CAD得分与结核病严重程度相关.
- 对AI-CAD而言,ROC曲线下的面积 (AUROC) 与细菌学参考相比为0.86.
- 人工智能-CAD使人类阅读和细菌学检查的需求分别减少了79%和85%,同时检测到95%的Xpert阳性结核病例.
结论:
- AI-CAD适用于基于社区的ACF,在高结核病负担的环境中,对专家阅读器的访问有限.
- 人工智能CAD可以扩大发展中国家的CXR查,减少工作量和劳动力.
- 需要进一步研究更大的样本大小和更多的读者来概括发现.
相关概念视频
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