Hybrid unsupervised representation learning and pseudo-label supervised self-distillation for rare disease imaging phenotype classification with dispersion-aware imbalance correction

Jinghan Sun, Dong Wei, Liansheng Wang, Yefeng Zheng

Abstract: Highlights•A simple yet effective approach to rare disease classification.•Eliminate the heavy burden of labeling the large base dataset.•Surprisingly superior performance to comparable supervised approaches.•Hybrid unsupervised and pseudo-label supervised self-distillation.•Dispersion-aware correction of inter-rare-disease performance imbalance.