Editor’s presentation: Towards a personalised approach in exercise-based cardiovascular rehabilitation: An European Association of Preventive Cardiology (EAPC) call for action

The health benefits of regular aerobic exercise are indisputable, and today exercise training is a cornerstone of cardiac and cancer rehabilitation programmes.1 In combination with other strategies, such as smoking cessation and healthy diet, exercise reduces symptoms, increases cardiopulmonary fitness, improves lipid profile, ameliorates blood pressure control, improves quality of life and reduces the incidence of sudden death and recurrent fatal myocardial infarction.2,–4 Access to and compliance with a cardiovascular rehabilitation programme are critical factors in the success of an exercise intervention, and the personalization of exercise prescription is mandatory in order to improve the efficacy of rehabilitation. In this issue, Gevaert and colleagues explain how to achieve a more personalized exercise prescription in light of the growing knowledge about the factors associated with inter-individual differences in the response to exercise. The authors also investigate the potential role of artificial intelligence in exercise prescription. In fact a machine learning algorithm based on the vast amount of data obtained from wearable devices in conjunction with clinical and laboratory parameters may provide a fully personalized exercise prescription.