NCT05967546

Deep Learning for Intelligent Identification of Arrhythmias

Deep Learning for Intelligent Identification of Arrhythmias (ECG-LEARNING): an Investigator-initiated, National Multicenter, Retrospective-prospective, Cohort Study

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 4,000 (estimated)
• Sponsor: First Affiliated Hospital Xi'an Jiaotong University · Academic / Other
• Sex: All
• Age: 3 Years
• Healthy volunteers: Not accepted

Summary

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

Detailed 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.

Conditions

• Arrhythmia

Interventions

Type	Name	Description
OTHER	Observational	No interventions will be given to patients.

Timeline

• Start date: 2024-12-30
• Primary completion: 2028-08-31
• Completion: 2028-12-31
• First posted: 2023-08-01
• Last updated: 2024-04-04

Locations

1 site across 1 country: China