EXPLAINABLE DEEP LEARNING METHOD FOR NON-INVASIVE DETECTION OF PULMONARY HYPERTENSION FROM HEART SOUNDS

The present document discloses a computer-implemented method for non-invasive estimation of Pulmonary Hypertension, PH, from heart sound signals, comprising the steps: receiving a sound signal acquired from a beating heart of a subject over a predetermined time period; generating one or more 2D feature maps comprising a 2D feature map with the received sound signal where a first axis of the map is arranged over time and a second axis of the map is arranged over individual heartbeats; applying a pre-trained neural network to relate the generated one or more 2D feature maps with a training dataset of previously acquired and generated training 2D feature maps of a PH subject group and a non-PH subject group, thus to obtain an indicator of the presence of Pulmonary Hypertension. It further discloses a training method of said neural network and a system.