Author

Toshio Shimokawa

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Preprint Sep 2026

BRP-GABLE: An Interpretable Rule-Based Prediction Framework for Multiple Outcome Types

Interpretable prediction models are important in biomedical research, where predictive accuracy must often be balanced against the ability to examine predictor-outcome relationships. Automatic Binary Logistic Estimation (ABLE) provides interpretable rule-based representations by constructing additive models using thres...

Yu-Long Li, Ke Wan, Toshio Shimokawa et al. · 0 citations

#machine learning Preprint Sep 2026

Geographically Regularized AUC-Maximizing Personalized Federated Learning

Accurate diagnostic and risk-prediction models are important for supporting clinical decision-making during infectious disease outbreaks. However, privacy and governance requirements may restrict patient-level data sharing across healthcare institutions, and data distributions often vary. Moreover, AUC is widely used t...

Mayu Hiraishi, Kensuke Tanioka, Toshio Shimokawa · 0 citations