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Article

AI-based derivation of atrial fibrillation phenotypes in the general and critical care populations.

EBioMedicine - 1 Sept 2024

Bellfield Ryan A A, Olier Ivan, Lotto Robyn, Jones Ian, Dawson Ellen A, Li Guowei, Tuladhar Anil M, Lip Gregory Y H, Ortega-Martorell Sandra

Abstract excerpt

BACKGROUND: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive accuracy is generally limited, given the inherent complexity and heterogeneity of patients with AF. By classifying different presentations of AF into coherent and...

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Source

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Identifiers

PMID: 39153412
DOI: 10.1016/j.ebiom.2024.105280
PMCID: PMC11381622

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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