A machine learning-based model for predicting paroxysmal and persistent atrial fibrillation based on EHR

A machine learning-based model for predicting paroxysmal and persistent atrial fibrillation based on EHR

Abstract Background There is no effective way to accurately predict paroxysmal and persistent atrial fibrillation (AF) subtypes unless electrocardiogram (ECG) observation is obtained. We aim to develop a predictive model using a machine learning algorithm for identification of paroxysmal and persist...

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Bibliographic Details
Main Authors: Yuqi Zhang, Sijin Li, Peibiao Mai, Yanqi Yang, Niansang Luo, Chao Tong, Kuan Zeng, Kun Zhang
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Atrial fibrillation
Paroxysmal atrial fibrillation
Persistent atrial fibrillation
Machine learning
Prediction model
Online Access:https://doi.org/10.1186/s12911-025-02880-5
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https://doi.org/10.1186/s12911-025-02880-5

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