通过人工智能 (AI) 诊断传染病:抗原测试阳性和新型AI驱动的喉内镜检测阳性之间的患者背景和症状的差异
Masahiko Mori1, Shinji Yoshinaga2, Tadayoshi Moriyama3
1Department of Internal Medicine, Sasebo Memorial Hospital, Sasebo, Nagasaki, Japan.
PLOS digital health
|February 11, 2026
概括
人工智能 (AI) 喉内镜和常规抗原 (Ag) 测试可以识别呼吸道感染的不同患者群体. 与年龄测试相比,AI测试确定了症状发病间隔较短和临床特征明显的患者.
科学领域:
- 医学诊断 医学诊断 医学诊断
- 医疗保健中的人工智能
- 传染病检测 发现 传染病检测
背景情况:
- 传统的快速抗原 (Ag) 测试可以检测流感/COVID-19 的病毒载量.
- 新型的人工智能 (AI) 驱动的喉内镜评估宿主免疫反应.
- 了解这些诊断方法之间的患者特征差异至关重要.
研究的目的:
- 通过传统的Ag测试与人工智能驱动的内镜检测呈阳性的个体之间的患者背景和症状的差异.
- 通过每种方法诊断的患者的临床概况进行比较.
主要方法:
- 813名患者接受了流感/COVID-19的Ag和AI内镜检测.
- 对患者人口统计,症状发作和临床表现的分析.
- 使用统计分析 (odds比率,p值) 进行测试阳性组的比较.
主要成果:
- 人工智能测试显示,总体上62%的人同意Ag测试.
- 艾滋病毒阳性病例的症状发作到测试间隔较短 (中位数为18小时与27小时).
- 艾滋病阳性病例更有可能是儿科病例,早些时候进行了测试,已知接触者,咳和发烧,但胃肠道症状较少.
结论:
- 人工智能和抗衰老测试捕获具有不同临床特征的不同患者群体.
- 人工智能专注于免疫反应,而Ag专注于病毒载荷影响诊断结果.
- 在23%的病例中,AI误诊COVID-19为流感,这是由于特定的喉病变解释.
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