PLOS ONE paper on deep learning techniques for the detection of lethal ventricular arrhythmia on out-of-hospital cardiac arrest patients

less than 1 minute read

Our paper “Mixed Convolutional and Long Short-Term Memory Network for the Detection of Lethal Ventricular Arrhythmia” was just published on PLOS ONE.


This is shared work between Tecnalia’s Computer Vision Group and the Research group on Bioengineering and Resuscitation (Biores) from the University of the Basque Country (UPV/EHU). The paper shows how, by applying a neural network comprising convolutional and LSTM modules, we can successfully detect lethal ventricular arrhythmia on Out-of-Hospital Cardiac Arrest (OHCA) patients.

More info and full text available here.