皮肤植物病的诊断准确性 暗示皮肤病特征的诊断准确性:用机器学习评估进行回顾性队列选择研究
Jack Hulse1, Richard Galbraith1, Tatiana Movchan1
1University of Missouri - Kansas City, School of Medicine, Kansas City, Missouri, USA.
Journal of cutaneous pathology
|January 13, 2026
概括
组织病理学特征可以表明皮肤菌感染,但它们的可靠性各不相同. 在H&E幻灯片上的角层中识别可能的真菌是皮肤植物病的最可靠的指标.
科学领域:
- 皮肤病理学 皮肤病理学
- 菌类学 菌类学是指菌类学.
- 历史学 历史学 历史学
背景情况:
- 组织病理学特征是皮肤菌感染的潜在指标.
- 这些特征的可靠性和准确性需要进一步调查.
研究的目的:
- 评估皮肤菌感染的组织病理学特征的观察者间可重复性和诊断准确性.
- 为了确定诊断皮肤植物病的最可靠的组织病理学线索.
主要方法:
- 四名盲目评估人员评估了97个H&E幻灯片,对12个潜在的皮肤植物病线索进行了评估.
- 计算了观察者之间的一致性和诊断准确性.
- 开发了机器学习模型,并使用五倍交叉验证进行了比较.
主要成果:
- 在大多数特征上发现了中等到实质性的协议,但在三明治标志和紧的红色角膜上发现了轻微的协议.
- 对皮肤细胞可疑的结构的存在是PAS阳性的唯一显著预测因素 (平衡精度=0.88).
- 使用疑似真菌的逻辑回归性能优于复杂的机器学习模型,在存在时产生0.93的阳性PAS概率.
结论:
- 在H&E染色部分的角层中可能存在的真菌菌是皮肤植物病的最可靠的本病学线索.
- 这一发现有助于准确诊断和管理真菌性皮肤感染.
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