  The article focuses on determining the predictive uncertainty of a model on
the example of atrial fibrillation detection problem by a single-lead ECG
signal. To this end, the model predicts parameters of the beta distribution
over class probabilities instead of these probabilities themselves. It was
shown that the described approach allows to detect atypical recordings and
significantly improve the quality of the algorithm on confident predictions.
