Juntendo University Feb 20 2026 Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used machine learning to analyze data from a nationwide registry of elderly HF patients. Their new model includes metrics of physical function and improved risk reclassification by about 20% compared to existing models, and could improve treatment options for patients in