Takahiro Kimura

Machine learning integrated explainable artificial intelligence in predicting toxicities of enfortumab vedotin in urothelial carcinoma: an exploratory study

Background Enfortumab vedotin (EV) therapy for advanced urothelial carcinoma is limited by adverse events (AEs). Early identification of high-risk patients is needed. This proof-of-concept study evaluated whether machine learning (ML) with explainable AI (SHAP) could predict EV t...

Clinical Impact of Gleason Pattern 5 on Doublet Versus Triplet Therapy in Metastatic Hormone‐Sensitive Prostate Cancer

BACKGROUND: Upfront treatment intensification with androgen deprivation therapy (ADT) plus an androgen receptor pathway inhibitor has become a standard approach for metastatic hormone-sensitive prostate cancer (mHSPC). However, prognosis remains poor for some patients despite sec...