Deep Learning for Intelligent Identification of Arrhythmias (ECG-LEARNING)

Xi'an Jiaotong University

Status

Not yet enrolling

Conditions

Arrhythmia

Treatments

Other: Observational

Study type

Observational

Funder types

Other

Identifiers

NCT05967546

XJTU1AF2023LSK-170

Details and patient eligibility

About

This study aims to design and train a deep learning model for the diagnosis of different arrhythmias.

Full description

This study aims to retrospectively and prospectively collect routine clinical data such as electrocardiograms from patients with arrhythmias who meet the inclusion and exclusion criteria. Then we will design and train a deep learning model to analyse the electrocardiographic features of the arrhythmias, and identify the types of arrhythmias and evaluate the value of the model for the diagnosis of different arrhythmias.

Enrollment

4,000 estimated patients

Sex

All

Ages

3+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

For retrospective study: 1.Patients with arrhythmia diagnosed by routine surface 12-lead electrocardiogram or Holter; 2.The type of arrhythmia is diagnosed by intracardiac electrophysiological examination.
For prospective study: 1.Patients with arrhythmia diagnosed by routine surface 12-lead electrocardiogram or Holter; 2.Intracardiac electrophysiological examination is planned.

Exclusion criteria

Lack of routine surface 12-lead electrocardiogram or holter data;
Lack of intracardiac electrophysiological examination;
Patients refused to sign informed consent and refused to participate in the study.