Machine Learning Improves the Prediction Rate of Non-Curative Resection of Endoscopic Submucosal Dissection in Patients with Early Gastric Cancer

Machine Learning Improves the Prediction Rate of Non-Curative Resection of Endoscopic Submucosal Dissection in Patients with Early Gastric Cancer

Non-curative resection (NCR) of early gastric cancer (EGC) after endoscopic submucosal dissection (ESD) can increase the burden of additional treatment and medical expenses. We aimed to develop a machine-learning (ML)-based NCR prediction model for EGC prior to ESD. We obtained data from 4927 patien...

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Bibliographic Details
Main Authors: Hae-Ryong Yun, Cheal Wung Huh, Da Hyun Jung, Gyubok Lee, Nak-Hoon Son, Jie-Hyun Kim, Young Hoon Youn, Jun Chul Park, Sung Kwan Shin, Sang Kil Lee, Yong Chan Lee
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Cancers
Subjects:
early gastric cancer
non-curative resection
machine learning
prediction
Online Access:https://www.mdpi.com/2072-6694/14/15/3742

Internet

https://www.mdpi.com/2072-6694/14/15/3742

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