Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation

Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation

Abstract Objective Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic complication in patients with atrial fibrillation (AF). This study aimed to evaluate the incidence and predictors of LAT in patients with paroxysmal AF, utilizing machine learning techniques ba...

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Bibliographic Details
Main Authors: Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team
Format: Article
Language:English
Published: BMC 2025-06-01
Series:BMC Cardiovascular Disorders
Subjects:
Paroxysmal atrial fibrillation
Left atrial thrombus
Transesophageal echocardiography
Machine-learning model
Online Access:https://doi.org/10.1186/s12872-025-04847-w
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