Machine learning-based unsupervised phenotypic clustering analysis of patients with IgA nephropathy: Distinct therapeutic responses of different groups

The unsupervised clustering method provided reliable classification of IgAN patients into different subgroups according to clinical features, prognoses, and treatment responsiveness. Our subgroup-based prediction model has significant clinical utility for the assessment of risk and treatment in patients with IgAN.