Identifying Diagnostic Biomarkers for Electroacupuncture Treatment of Rheumatoid Arthritis Using Bioinformatic Analysis and Machine Learning Algorithms

This study employed three machine learning algorithms to identify potential diagnostic biomarkers for the alleviation of RA by EA. The biomarkers demonstrated robust diagnostic performance across multiple validation datasets. Furthermore, animal experiments confirmed that EA exerted a favorable regulatory effect on these diagnostic biomarkers. The findings of this study provided novel therapeutic targets for the EA treatment of RA.