Development of machine learning models for predicting depressive symptoms in knee osteoarthritis patients.

ABSTRACT: Knee osteoarthritis (KOA) combined with depressive symptoms is prevalent and leads to poor outcomes and significant financial burdens. However, practical tools for identifying at-risk patients remain limited. A robust prediction model is needed to address this gap. This study aims to develop and validate a predictive model to identify KOA patients at risk of developing depressive symptoms. The China Health and Retirement Longitudinal Survey (CHARLS) data were used for model development and the Osteoarthritis Initiative (OAI) for external validation. 18 potential predictors were selected using LASSO regression. 4 machine learning models-logistic regression, decision tree, random forest, and artificial neural network-were developed. Model performance was assessed using the area under the ope

SUBMITTER: Li D 

PROVIDER: S-EPMC11577092 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature