Prediction of atrial fibrillation admissions in arrhythmia naïve patients from structured electronic health record data

Abstract Background Atrial fibrillation (AF) is the most prevalent sustained arrhythmia, but its diagnosis is often elusive. In this study, we examined the role of machine learning (ML) algorithms in predicting AF in arrhythmia-naïve patients, based on structured domains of the electronic health rec...

Full description

Bibliographic Details

Published in:	BMC Medical Informatics and Decision Making
Main Authors:	Tanmay Gokhale, Nirav R. Bhatt, Matthew Starr, Suresh Mulukutla, Floyd Thoma, Murat Akcakaya, Salah Al-Zaiti, Raul G. Nogueira, Samir Saba
Format:	Article
Language:	English
Published:	BMC 2025-09-01
Subjects:	Atrial fibrillation Electronic health records Prediction Admission Machine learning
Online Access:	https://doi.org/10.1186/s12911-025-03199-x