The research group of Prof. Yael Yaniv of the Faculty of Biomedical Engineering at the Technion-Israel Institute of Technology in Haifa joined forces with the research groups of Prof. Alex Bronstein and Prof. Assaf Schuster of the Taub Faculty of Computer Science to create an AI-based system that automatically detects disease based on hundreds of electrocardiograms, which are currently the most widespread technology employed for the diagnosis of cardiac pathology.
The new system automatically analyzes electrocardiograms (ECGs) using augmented neural networks – the most prominent tool in deep learning today. These networks learn different patterns by training on a large number of samples, and the system developed by the researchers was trained on more than 1.5 million ECG segments sampled from hundreds of patients in hospitals in various countries.
The system is sensitive enough to provide alerts regarding patients at risk of arrhythmia (irregular heartbeat) – even when the arrhythmia is not shown on the ECG printout. In addition, the rate of false alarms is very minimal. The new system also explains its decisions using the accepted cardiology terminology.
Originally posted at vfinews.com