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We present the identification problem as a global optimization challenge by minimizing the mismatch between the ECG predicted by a cardiac model when paced at a certain EAS and the observed ECG during the ectopic activity. With the lead field approach for computing the ECG, our cardiac model attempts to solve an anisotropic eikonal equation for cardiac activation and the forward bidomain model in the torso. To perform Bayesian optimization, we develop a Gaussian process survivor model of the loss function on the heart surface.
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