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Machine‐Learning Prediction of Bleeding After Endoscopic Submucosal Dissection for Early Gastric Cancer: A Multicenter Study

ABSTRACT Background Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer (GC); however, post‐ESD bleeding remains a serious and unpredictable complication. This study aimed to develop machine‐learning (ML) models to predict post‐ESD bleeding and identify...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Hiroki Maruyama, Kazuya Takahashi, Kosuke Kojima, Nao Nakajima, Hiroki Sato, Ken‐ichi Mizuno, Soichi Sugitani, Shuji Terai
Format: Artigo
Sprache:Inglês
Veröffentlicht: Wiley 2025-07-01
Schriftenreihe:JGH Open
Schlagworte:
artificial intelligence
bleeding
early gastric cancer
endoscopic submucosal dissection
feature importance
machine learning
Online-Zugang:https://doi.org/10.1002/jgh3.70203
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