Artificial intelligence and atrial fibrillation.

ABSTRACT:

Background

In the context of atrial fibrillation (AF), traditional clinical practices have thus fallen short in several domains, such as identifying patients at risk of incident AF or patients with concomitant undetected paroxysmal AF. Novel approaches leveraging artificial intelligence have the potential to provide new tools to deal with some of these old problems.

Aims

To discuss the roles of artificial intelligence (AI)-enabled electrocardiogram (ECG) pertaining to AF, potential roles of deep learning (DL) models in the context of current knowledge gaps, as well as limitations of these models.

Materials & methods

An extensive search and review of the currently available literature on the topics.

Results

One key area where DL models can translate to better pa

SUBMITTER: Sehrawat O 

PROVIDER: S-EPMC9717694 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature