AI-Based Differential Diagnosis and Localization of Tachycardia Using ECG: Multicenter Registry (EP-AI ASSIST)

RECRUITING

NCT07859020

Sponsor: Inha University Hospital

Summary

This multicenter retrospective study aims to develop, validate, and clinically apply an artificial intelligence (AI)-powered electrocardiography (ECG) algorithm for the diagnosis and prognostic prediction of cardiovascular diseases, including coronary artery disease and heart failure. By utilizing encrypted raw 12-lead ECG text data and deep neural network models, the study evaluates the effectiveness of AI-enhanced ECG in detecting cardiac abnormalities and predicting clinical outcomes.

Official title: AI-based Differential Diagnosis and Localization of Tachycardia Using ECG: Multicenter Registry (EP-AI ASSIST)

Key Details

Gender

All

Age Range

19 Years - Any

Study Type

OBSERVATIONAL

Enrollment

10000

Start Date

2023-12-01

Completion Date

2028-12-01

Last Updated

2026-10-05

Healthy Volunteers

No

Conditions

Tachycardia Paroxysmal Supraventricular Tachycardia Wolff-Parkinson-White Syndrome Premature Ventricular Contractions Ventricular Tachycardia

Interventions

DIAGNOSTIC_TEST

AI-based ECG Diagnostic and Localization Algorithm

Application of a deep learning-based 12-lead electrocardiogram (ECG) algorithm to analyze raw text data for the differential diagnosis and localization of tachycardias, including PSVT, WPW syndrome, PVC, and VT\[cite: 1\].

Locations (1)

Inha University Hospital

Incheon, Incheon, South Korea

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