A risk model to predict atrial fibrillation in diabetes using machine learning: The ACCORD study

Background: Machine learning (ML) may improve prediction of atrial fibrillation (AF), but its value compared with traditional models such as Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE-AF) in patients with diabetes remains unclear. Methods: Among 9,307 patients in the Action...

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Principais autores:	Erik J. Offerman, Joseph Phan, Sarah Harirforoosh, Wenjun Fan, Nathan D. Wong, David M. Donaldson
Format:	Artigo
Jezik:	Inglês
Izdano:	Elsevier 2026-02-01
Serija:	American Heart Journal Plus
Teme:	Atrial fibrillation Machine learning Random forest Diabetes mellitus Risk prediction Cardiovascular epidemiology
Online dostop:	http://www.sciencedirect.com/science/article/pii/S2666602226000030
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