The objective of this study is to develop artificial intelligence (AI) tools to characterize cardiac remodelling in arterial hypertension through the analysis of routine imaging data (echocardiography) coupled with patient data. More precisely, this study will make it possible (i) to represent in a relevant way the spectrum of the cardiac repercussions of a population affected by hypertension to better characterize the progress of the pathology, in particular vis-à-vis the more ambiguous subjects to be characterized (grey area); (ii) to develop tools for the automatic quantification of cardiac function (segmentation and robust monitoring of the myocardium during the cardiac cycle, for the dynamic analysis of the shape and global deformation of the heart) and therefore to extract descriptors richer in cardiac function than those currently used in clinical routine.