Enhancing diagnosis of Hirschsprung’s disease using deep learning from histological sections of post pull-through specimens: preliminary results

PURPOSE: Accurate histological diagnosis in Hirschsprung disease (HD) is challenging, due to its complexity and potential for errors. In this study, we present an artificial intelligence (AI)-based method designed to identify ganglionic cells and hypertrophic nerves in HD histology. METHODS: Formali...

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Detalles Bibliográficos
Autores principales: Duci, Miriam, Magoni, Alessia, Santoro, Luisa, Dei Tos, Angelo Paolo, Gamba, Piergiorgio, Uccheddu, Francesca, Fascetti-Leon, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687181/
https://www.ncbi.nlm.nih.gov/pubmed/38019366
http://dx.doi.org/10.1007/s00383-023-05590-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687181/
https://www.ncbi.nlm.nih.gov/pubmed/38019366
http://dx.doi.org/10.1007/s00383-023-05590-z

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