Development and technical validation of an artificial intelligence model for quantitative analysis of histopathologic features of eosinophilic esophagitis

BACKGROUND: In an attempt to provide quantitative, reproducible, and standardized analyses in cases of eosinophilic esophagitis (EoE), we have developed an artificial intelligence (AI) digital pathology model for the evaluation of histologic features in the EoE/esophageal eosinophilia spectrum. Here...

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Detalles Bibliográficos
Autores principales: Archila, Luisa Ricaurte, Smith, Lindsey, Sihvo, Hanna-Kaisa, Westerling-Bui, Thomas, Koponen, Ville, O’Sullivan, Donnchadh M., Fernandez, Maria Camila Cardenas, Alexander, Erin E., Wang, Yaohong, Sivasubramaniam, Priyadharshini, Patil, Ameya, Hopson, Puanani E., Absah, Imad, Ravi, Karthik, Mounajjed, Taofic, Pai, Rish, Hagen, Catherine, Hartley, Christopher, Graham, Rondell P., Moreira, Roger K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577132/
https://www.ncbi.nlm.nih.gov/pubmed/36268110
http://dx.doi.org/10.1016/j.jpi.2022.100144

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577132/
https://www.ncbi.nlm.nih.gov/pubmed/36268110
http://dx.doi.org/10.1016/j.jpi.2022.100144

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