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Updated: Sep 9, 2025

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基于视觉和人工智能的COVID-19肺炎评估:已建立的半量化胸部CT评分系统的可行性和可重现性

Eugen Neumann¹, Anna Movlilishvili¹, Simon T Scherfeld¹

¹Department of Diagnostic and Interventional Radiology, Klinikum Lippe, Medical School and University Medical Center OWL, Bielefeld University, 32756 Detmold, Germany.

Diagnostics (Basel, Switzerland)

|August 28, 2025

概括

评估COVID-19肺部影响的Pan-score系统显示了人类读者与人工智能之间的高度一致. 尽管有些主观性,但它提供了一种可靠的方法来评估肺部疾病的严重程度.

科学领域:

放射学
人工智能
传染性疾病

背景情况:

评估COVID-19肺部感染的严重程度对于患者管理至关重要.
泛评分是一种半定量系统,用于评估胸部CT的肺部疾病.
视觉和基于人工智能的评分需求评估的评审者间协议.

研究的目的:

为了确定Pan-score系统的评价者之间的协议.
将人类读者的视觉评估与基于人工智能的评估进行比较.
评估COVID-19患者的泛评分的可靠性.

主要方法:

对569名COVID-19患者进行胸部CT扫描后期研究.
由放射科医生,助理医生,医学学生和人工智能软件分配的泛评分.
权衡的科恩卡帕 (κ) 计算为评价者之间的一致性.

主要成果:

在人类读者 (κ = 0.710.86) 和人类与人工智能 (κ = 0.83) 之间观察到高互评分一致性.
基于人工智能的分数明显高于人类评估的分数 (p < 0. 001).
图像切片厚度没有影响共识;对比介质的使用增加了分数.

结论:

泛评分是用户友好的,但可能是主观的,导致潜在的不准确.
较高的互评分协议支持COVID-19肺部参与的泛评分的可靠性.
人类读者和人工智能都表现出Pan-score系统的一致性.

关键词:

基于人工智能的评估冠状病毒肺炎 CT评分系统胸部CT 读者之间的协议

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