Actively Recruiting
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
Led by National Defense Medical Center, Taiwan · Updated on 2026-02-24
8666
Participants Needed
1
Research Sites
19 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
This study aims to validate the use of an artificial intelligence-enabled electrocardiogram (AI-ECG) to screen for elevated PAP. We hypothesize that the AI-ECG model can early identify patients with pulmonary hypertension in high-risk patients, prompting further evaluation through echocardiography, potentially resulting in improving cardiovascular outcomes.
CONDITIONS
Official Title
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Men or women, 50 to 85 years of age
- At least one 12-lead ECG within 3 months
You will not qualify if you...
- Diagnosis of pulmonary hypertension WHO Groups 1, 2, 3, 4, or 5
- Diagnosis of hypertrophic cardiomyopathy, restrictive cardiomyopathy, constrictive pericarditis, cardiac amyloidosis, or infiltrative cardiomyopathy
- Prior heart, lung, or heart-lung transplant
- Systolic pulmonary artery pressure >50 mmHg by echocardiography before
- Echocardiography in 3 months before index ECG
AI-Screening
AI-Powered Screening
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Trial Site Locations
Total: 1 location
1
National Defense Medical Center
Taipei, Taiwan
Actively Recruiting
Research Team
C
Chin Lin, Associate Professor
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
DIAGNOSTIC
Number of Arms
2
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