Development of automated machine learning models in predicting colorectal adenoma in metabolic-associated steatotic liver disease

BackgroundMetabolic-associated steatotic liver disease (MASLD) is recognized as the most common chronic liver disease worldwide. Identification of colorectal adenoma in MASLD is crucial to enable patients to take necessary preventive colonoscopy screening and treatment earlier. The main objective of...

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Autori principali:	Lu Liu, Huixian Zhang, Ziyu Zhao, Chunfang Xu, Shuting Qu
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Frontiers Media S.A. 2026-05-01
Serie:	Frontiers in Medicine
Soggetti:	clinical predictive models colorectal adenoma machine learning non-alcoholic fatty liver disease SHAP (Shapley Additive Explanations)
Accesso online:	https://www.frontiersin.org/articles/10.3389/fmed.2026.1852441/full
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