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Background Currently available sudden cardiac death (SCD) risk screening methods based on heart-rate dynamics fail to identify most high-risk patients and cannot guide further prophylactic interventions effectively in post-acute myocardial infarction (AMI) population.In this paper,we propose to develop a Bayesian parametric approach by combining predictive power of multivariate heart-rate dynamics parameters for improvement of risk stratification after an AMI.