Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression.

ABSTRACT: The controversy surrounding whether serum total cholesterol is a risk factor for the graded progression of knee osteoarthritis (KOA) has prompted this study to develop an authentic prediction model using a machine learning (ML) algorithm. The objective was to investigate whether serum total cholesterol plays a significant role in the progression of KOA. This cross-sectional study utilized data from the public database DRYAD. LASSO regression was employed to identify risk factors associated with the graded progression of KOA. Additionally, six ML algorithms were utilized in conjunction with clinical features and relevant variables to construct a prediction model. The significance and ranking of variables were carefully analyzed. The variables incorporated in the model include JBS3, Diabetes

SUBMITTER: Li HB 

PROVIDER: S-EPMC11324727 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature