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...

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Autors principals:	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
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2024-12-01
Col·lecció:	Scientific Reports
Matèries:	Artificial intelligence Celiac disease Histology Machine learning
Accés en línia:	https://doi.org/10.1038/s41598-024-79570-1
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