Placing first the PhysioNet/CinC Challenge 2017 was “Black Swan,” an international team of researchers led by Morteza Zabihi, a biomedical engineering postgraduate at Tampere University of Technology, and Ali Bahrami Rad, a postdoctoral...
ENCASE combines deep neural networks and expert features together for AF Classification from a short single lead ECG recording. It won the First Place in the PhysioNet/Computing in Cardiology Challenge 2017 (https://physionet.org/challenge/2017), with an overall F1 score of 0.83. The original ...