Deep-Learning for the Diagnosis of Esophageal Cancers and Precursor Lesions in Endoscopic Images: A Model Establishment and Nationwide Multicenter Performance Verification Study

Background: Suspicion of lesions and prediction of the histology of esophageal cancers or premalignant lesions in endoscopic images are not yet accurate. The local feature selection and optimization functions of the model enabled an accurate analysis of images in deep learning. Objectives: To establ...

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Detalles Bibliográficos
Autores principales: Gong, Eun Jeong, Bang, Chang Seok, Jung, Kyoungwon, Kim, Su Jin, Kim, Jong Wook, Seo, Seung In, Lee, Uhmyung, Maeng, You Bin, Lee, Ye Ji, Lee, Jae Ick, Baik, Gwang Ho, Lee, Jae Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320232/
https://www.ncbi.nlm.nih.gov/pubmed/35887549
http://dx.doi.org/10.3390/jpm12071052

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320232/
https://www.ncbi.nlm.nih.gov/pubmed/35887549
http://dx.doi.org/10.3390/jpm12071052

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