Advancing Personalized Medicine For Ventricular Arrhythmias
Researchers are working to improve personalized medicine and predict risk for ventricular arrhythmias with whole-heart computational models.
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- To better understand ventricular arrhythmias, Johns Hopkins University researchers are studying the use of whole-heart computational models. Whole-heart computational modeling can lead to personalized medicine and predict a patient’s risk of sudden cardiac death or outcomes of cardiac procedures.
Whole-heart ventricular modeling is currently witnessing an evolution of a variety of computational approaches, especially when pursuing personalized treatment and technologies. Ventricular arrhythmias are one of the leading causes of mortality worldwide. With whole-health computational models, researchers hope to gain a better understanding of the heart condition.
The researchers described using various computational approaches to address the mechanisms of cardiac dysfunction and problems related to the clinical application of computation-drive diagnostic and therapeutic approaches for cardiac disease and arrhythmias.