Algorithm for search of abnormalities in populations of cardiomyocyte mathematical models

During the last 40 years a lot of mathematical models were developed for simulation of cardiomyocytes electrophysiology. In this work we propose an algorithm for meta-analysis of these models. Using pairwise comparison, our approach searches for outliers in model predictions that can be obtained in one model, but not in the other. Here, we analyzed four models of the atrial cardiomyocytes with the proposed approach. Our results show significant differences in the ability of models to simulate the delayed afterdepolarization, early afterdepolarization, sustained triggered activity, and the failure of activation. The proposed approach may be useful for the comparison of two models and for obtaining additional rejection criteria for studies with the model populations. Such criteria may improve the reliability of mathematical model predictions.