Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms

Background and aimsSessile serrated lesions (SSLs) are morphologically subtle and often misclassified as hyperplastic polyps (HPs), increasing colorectal cancer risks. We developed a machine learning (ML) model to improve endoscopic SSL diagnosis.MethodsThree hundred and eighty-six colorectal polyps...

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Bibliographic Details

Published in:	Frontiers in Medicine
Main Authors:	Xinying Yu, Lianyu Li, Qiang He
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-10-01
Subjects:	sessile serrated lesion artificial intelligence machine learning colorectal polyps hyperplastic polyps
Online Access:	https://www.frontiersin.org/articles/10.3389/fmed.2025.1665079/full