Predicting relapse in pediatric IgA vasculitis in the era of machine learning: an explainable hybrid ensemble model.
OBJECTIVES This study aimed to develop an explainable hybrid ensemble machine learning (ML) model to predict relapse in pediatric IgA vasculitis (IgAV) using routine clinical and laboratory data. METHODS This retrospective cohort study included 653 children diagnosed with IgAV according to EULAR/PRINTO/PRES criteria....