Can deep-learning algorithms applied to ECG data identify right and left ventricular dysfunction?
Deep learning applied to ECGs may serve as an inexpensive tool to screen and diagnose both left and right ventricular dysfunction.
DL on ECG data can be used to create inexpensive screening, diagnostic, and predictive tools for both LV and RV dysfunction. Such tools may bridge the applicability of ECGs and echocardiography and enable prioritization of patients for further interventions for either sided failure progressing to biventricular disease.
Vaid et al. (Thu,) studied this question.