AI-Driven Biological Clock Predicts Health Outcomes and Diseases
This study introduces LifeClock, a comprehensive biological aging clock based on routine clinical data from electronic health records (EHRs), utilizing a transformer-based model called EHRFormer to predict biological age across the full human lifespan and assess its association with disease risks and survival outcomes, demonstrating high accuracy and potential for personalized medicine.