Advanced data analytics workflow in echocardiography: application in patients with aortic stenosis

Recent studies based on machine learning techniques suggest that the identification of phenotypes or clusters of several variables provide useful insights for several cardiac diseases, particularly in aortic stenosis (AS). Imaging data derived from echocardiography as the main imaging modality in this setting is a key component of these phenotypes. However, translation of this novel knowledge into clinical practice is complex and requires new data workflows with advanced analytics capabilities.