Predicting cardiac disease from interactions of simultaneously-acquired hemodynamic and cardiac signals

Abstract

Nonlinear features from simultaneously-acquired signals used as inputs to machine learning can assess CAD and LVEDP safely and accurately with an easy-to-use, portable device, utilized at the point-of-care without radiation, contrast, or patient preparation.