No-Code Platform-Based Deep-Learning Models for Prediction of Colorectal Polyp Histology from White-Light Endoscopy Images: Development and Performance Verification

Background: The authors previously developed deep-learning models for the prediction of colorectal polyp histology (advanced colorectal cancer, early cancer/high-grade dysplasia, tubular adenoma with or without low-grade dysplasia, or non-neoplasm) from endoscopic images. While the model achieved 67...

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Detalles Bibliográficos
Autores principales: Gong, Eun Jeong, Bang, Chang Seok, Lee, Jae Jun, Seo, Seung In, Yang, Young Joo, Baik, Gwang Ho, Kim, Jong Wook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9225479/
https://www.ncbi.nlm.nih.gov/pubmed/35743748
http://dx.doi.org/10.3390/jpm12060963

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9225479/
https://www.ncbi.nlm.nih.gov/pubmed/35743748
http://dx.doi.org/10.3390/jpm12060963

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