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A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension

NCT07079592 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 8666

Last updated 2026-02-24

No results posted yet for this study

Summary

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

  • Artificial Intelligence (AI)
  • Artificial Intelligence (AI) in Diagnosis
  • Hypertension, Pulmonary

Interventions

DIAGNOSTIC_TEST

AI-ECG Guidance

Participants undergo screening using the AI-ECG system. Those identified as high-risk for pulmonary hypertension receive echocardiography to confirm the diagnosis and guide subsequent management.

Sponsors & Collaborators

  • National Defense Medical Center, Taiwan

    lead OTHER

Principal Investigators

  • Chin Lin, associate professor · National Defense Medical Center, Taiwan

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
50 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-02-28
Primary Completion
2026-06-15
Completion
2026-06-15

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07079592 on ClinicalTrials.gov