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Starting soon Observational

Deep Learning for Intelligent Identification of Arrhythmias

NCT05967546 · tracked via the Priya Life Science China tracker
Phase
Observational
Started
2024-12-30
Last updated
2024-04-04

Condition(s) studied

Arrhythmia

Investigational drug(s) / intervention(s)

Observational

Observational: No interventions will be given to patients.

Study summary

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

Eligibility

Sex
ALL
Min age
3 Years
Max age
—
Healthy volunteers
No
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.

Primary outcome measure(s)

  • A deep learning model designed to intelligently identify the types of arrhythmia. — 1 day after the enrollment.
    The model is trained on the training set, the best model and hyperparameters are selected through the verification set, and finally the model results are tested on the test set.

Trial sites (1)

FacilityCityRegionStatus
First Affiliated Hospital of Xi'an Jiantong University Xi'an Shaanxi
Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT05967546 on ClinicalTrials.gov ↗ ← All trials in China