Integrated computer modelling of cardiorespiratory fitness for personalised risk profiling and heart failure prevention (iCAREFIT) KU Leuven
Cardiology, Research Group for Rehabilitation in Internal Disorders, Hypertension and Cardiovascular Epidemiology
Clinical exercise tests could improve the personalized risk profiling and management of cardiovascular disease. Yet, current practice only considers a limited selection of cardiopulmonary exercise indexes in isolation. To utilize the full value of clinical exercise testing data, we will apply advanced machine learning (ML) approaches on big data that has been collected/will be collected in patients at UZ Leuven (n=1800) and within the general ...