A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification

Abstract Histological assessment is essential for the diagnosis and management of celiac disease. Current scoring systems, including modified Marsh (Marsh–Oberhuber) score, lack inter-pathologist agreement. To address this unmet need, we aimed to develop a fully automated, quantitative approach for...

وصف كامل

التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Michael Griffin, Aaron M. Gruver, Chintan Shah, Qasim Wani, Darren Fahy, Archit Khosla, Christian Kirkup, Daniel Borders, Jacqueline A. Brosnan-Cashman, Angie D. Fulford, Kelly M. Credille, Christina Jayson, Fedaa Najdawi, Klaus Gottlieb
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	Nature Portfolio 2024-12-01
سلاسل:	Scientific Reports
الموضوعات:	Artificial intelligence Celiac disease Histology Machine learning
الوصول للمادة أونلاين:	https://doi.org/10.1038/s41598-024-79570-1
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!