AI for Precision Medicine explores how artificial intelligence can advance personalized healthcare by integrating genomic, clinical, and imaging data to predict disease risks and tailor treatments to individual patients. The research combines cutting-edge machine learning with bioinformatics and e-health approaches to develop tools that improve diagnosis, treatment, and prevention strategies, ultimately supporting more precise and effective healthcare interventions.
This subgroup focuses on identifying genetic markers and disease patterns to better understand complex conditions such as cancer, cardiovascular disease, and diabetes.
This subgroup uses AI and machine learning to analyze clinical, genomic, and wearable data to tailor treatments and improve drug efficacy for individual patients.