Russian and US scientists have used machine learning to find ‘atrial fibrillation (AF) drivers’ – small patches of faulty heart muscle that can cause cardiac arrhythmia. The team tested their approach on 11 donated human hearts and located AF drivers with an accuracy of up to 81%. Multi-electrode mapping (MEM) is a technique that can ...
This story continues at Machine learning finds heart faults
Or just read more coverage at Electronics Weekly