Keywords: geometric deep learning, graph neural networks
TL;DR: We develop and test a new Geometric Deep Learning (GDL) approach to infer BP data
Abstract: A correct measurement of the Blood Pressure (BP) is crucial in monitoring the health status of a patient and in diagnosis of cardiac vascular diseases. In this proof of concept, we develop and test a new Geometric Deep Learning (GDL) approach to infer BP data from other biological parameters: the photoplethysmogram and the electrocardiogram (ECG). Our findings suggest that such a GDL approach shows great promise compared with many state of the art models that are used in the field.