Stanford Researchers Tackle Cardiac Arrhythmia Detection with Machine Learning

Stanford Researchers Tackle Cardiac Arrhythmia Detection with Machine Learning

By John Russell Using machine learning techniques Stanford University researchers reported developing an algorithm for identifying cardiac arrhythmias that performs as well or better than cardiologists. Training the model, as usual, was the big hurdle. The researchers used a 34-layer convolutional neural network (CNN) to train a model able to distinguish 14 types of arrhythmias.