Utility of a deep learning model and a clinical model for predicting bleeding after endoscopic submucosal dissection in patients with early gastric cancer

BACKGROUND: Bleeding is one of the major complications after endoscopic submucosal dissection (ESD) in early gastric cancer (EGC) patients. There are limited studies on estimating the bleeding risk after ESD using an artificial intelligence system. AIM: To derivate and verify the performance of the...

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Detalles Bibliográficos
Autores principales: Na, Ji Eun, Lee, Yeong Chan, Kim, Tae Jun, Lee, Hyuk, Won, Hong-Hee, Min, Yang Won, Min, Byung-Hoon, Lee, Jun Haeng, Rhee, Poong-Lyul, Kim, Jae J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2022
Materias:
Retrospective Cohort Study
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260866/
https://www.ncbi.nlm.nih.gov/pubmed/35979158
http://dx.doi.org/10.3748/wjg.v28.i24.2721

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260866/
https://www.ncbi.nlm.nih.gov/pubmed/35979158
http://dx.doi.org/10.3748/wjg.v28.i24.2721

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