Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles

Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles

<b>Background:</b> Employing advanced machine learning models, we aim to identify biomarkers for urolithiasis from 24-h metabolic urinary abnormalities and study their associations with urinary stone diseases. <b>Methods:</b> We retrospectively recruited 468 patients at Pekin...

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Bibliographic Details
Main Authors: Lin Ma, Yi Qiao, Runqiu Wang, Hualin Chen, Guanghua Liu, He Xiao, Ran Dai
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Metabolites
Subjects:
machine learning
urinary stone diseases
metabolites
biomarkers
random forest
Online Access:https://www.mdpi.com/2218-1989/14/12/674

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https://www.mdpi.com/2218-1989/14/12/674

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