Predicting Future Incidences of Cardiac Arrhythmias Using Discrete Heartbeats from Normal Sinus Rhythm ECG Signals via Deep Learning Methods

Predicting Future Incidences of Cardiac Arrhythmias Using Discrete Heartbeats from Normal Sinus Rhythm ECG Signals via Deep Learning Methods

This study aims to compare the effectiveness of using discrete heartbeats versus an entire 12-lead electrocardiogram (ECG) as the input for predicting future occurrences of arrhythmia and atrial fibrillation using deep learning models. Experiments were conducted using two types of inputs: a combinat...

Full description

Bibliographic Details
Main Authors: Yehyun Kim, Myeonggyu Lee, Jaeung Yoon, Yeji Kim, Hyunseok Min, Hyungjoo Cho, Junbeom Park, Taeyoung Shin
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Diagnostics
Subjects:
arrhythmia risk prediction
atrial fibrillation risk prediction
artificial intelligence
Online Access:https://www.mdpi.com/2075-4418/13/17/2849

Internet

https://www.mdpi.com/2075-4418/13/17/2849

Similar Items