Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

ABSTRACT: We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often through catheter ablation, which involves the targeted localised destruction of regions of the myocardium responsible for initiating or perpetuating the arrhythmia. Ablation targets are either anatomically defined, or identified based on their functional properties as determined through the analysis of contact intracardiac electrograms acquired with increasing spatial density by modern electroanatomic mapping systems. While numerous quantitative approaches have been investigated over the past decades for identifying these critical curative sites,

SUBMITTER: Cantwell CD 

PROVIDER: S-EPMC6334203 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature