将结核症状查与胸部X射线与人工智能进行比较,用于尼日利亚东北部的活跃病例发现活动
Stephen John1, Suraj Abdulkarim2, Salisu Usman3
1Janna Health Foundation, Yola, Adamawa State, Nigeria.
BMC global and public health
|December 16, 2024
概括
超便携式X射线和AI在偏远地区有效查结核病 (TB),优于基于症状的方法. 人工智能辅助的胸部X射线改善了病例发现,并降低了难以到达的人群的诊断成本.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 公共卫生 公共卫生
背景情况:
- 在偏远人口中对结核病 (TB) 的查存在挑战.
- 带有人工智能的超便携式X射线 (CXR) 设备为活跃结核病例的发现提供了潜在的解决方案.
- 有限的研究已经评估了这些技术的现实性能.
研究的目的:
- 评估胸部X射线 (CXR) 和症状查的性能,以发现活跃的结核病例.
- 评估超便携式X射线和人工智能在偏远人口中的实用性.
- 为了比较不同组合的症状和AI解释的CXR用于结核病查.
主要方法:
- 在尼日利亚东北部的农村地区,针对15岁及以上的个人进行了查营.
- 使用了由AI (qXR V3) 解释的超便携式CXR (MinXray Impact系统).
- 根据AI分数或报告的症状,收集液样本进行Xpert MTB/RIF测试.
主要成果:
- 5297人进行了查;85人 (8%) 检测出结核病阳性.
- 仅仅通过症状查就能发现90.6%的结核病例,但其特异性较低 (11.4%).
- 人工智能异常得分为0.50,发现89.4%的结核病例具有改善的特异性 (62.8%).
结论:
- 超便携式CXR与人工智能在服务不足的地区对结核病查有效.
- 仅仅症状查不足以全面发现结核病例.
- 人工智能对CXR的解释提高了分拣效率,并降低了诊断成本,特别是在人类读者稀缺的地方.
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