A machine learning framework automatically identifies prognostically distinct patient subgroups across cancer types by optimizing directly for survival heterogeneity, without prior knowledge of established risk factors. Original paper: Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence. — NPJ digital medicine. 10.1038/s41746-026-02663-w 📄 Read the article