Machine Learning Classification of Inflammatory Bowel Disease in Children Based on a Large Real-World Pediatric Cohort CEDATA-GPGE® Registry

Introduction: The rising incidence of pediatric inflammatory bowel diseases (PIBD) facilitates the need for new methods of improving diagnosis latency, quality of care and documentation. Machine learning models have shown to be applicable to classifying PIBD when using histological data or extensive...

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Detalles Bibliográficos
Autores principales: Schneider, Nicolas, Sohrabi, Keywan, Schneider, Henning, Zimmer, Klaus-Peter, Fischer, Patrick, de Laffolie, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180568/
https://www.ncbi.nlm.nih.gov/pubmed/34109197
http://dx.doi.org/10.3389/fmed.2021.666190

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180568/
https://www.ncbi.nlm.nih.gov/pubmed/34109197
http://dx.doi.org/10.3389/fmed.2021.666190

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