Predicting arthritis risk with machine learning: Insights from the 2023 National Health Interview Survey data.

ABSTRACT: Arthritis, a common chronic disease encompassing multiple subtypes of osteoarthritis and rheumatoid arthritis, was explored in this study as a risk-related factor based on data from the 2023 U.S. National Health Interview Survey (NHIS). The study included 26,031 participants (6,849 in the arthritis group; 19,182 in the control group), and 21 variables were found to be significantly different between groups by chi-square test. Fourteen key predictors were screened using support vector machine recursive feature elimination (SVM-RFE): age, general health, chronic obstructive pulmonary disease, gender, hypertension, coronary heart disease, body mass index (BMI), cancer, depression, dementia, asthma, diabetes, smoking status, and hepatitis. The column-linear graphical model constructed based on

SUBMITTER: Chen T 

PROVIDER: S-EPMC12654921 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature