I heard before that a problem with heart monitoring for ML is that most of the samples out there are with abnormal hearts rather than normal and false alarms. As in, there's not enough published data to establish a baseline for high accuracy across general population. Most claims like this cite rules protecting medical records/data. Never got to ask a specialist in the field for confirmation or rejection of that claim.
True -- the available data sets (like MIT-BIH arrhythmia database) are quite small. In our case, we launched a study with UCSF Cardiology which has recruited about 10,000 people so far, and that's how we get a data set large enough for deep learning.
So, how true or false is it?