Using Artificial Intelligence on Heart Tracings to Detect and Predict Heart Disease
Studies past heart tracings with artificial intelligence to find heart disease in adults.
Plain-language title generated from the registry record
Registry title: AI-Powered Electrocardiography for Diagnosis and Prognostic Prediction in Cardiovascular Disease (AI-CVD): Multicenter Retrospective Study
Key facts
- Where
- Incheon, South KoreaSee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The study uses past ECG records of adults diagnosed with heart and blood vessel diseases, such as coronary artery disease and heart failure.
- Age
- 18 years or older
- Sex
- All sexes
- Disease stage
- Diagnosed cardiovascular disease, including coronary artery disease and heart failure
- Biomarker or test result
- A 12-lead ECG record that can be extracted as text
Main reasons for not taking part
- People the investigator judges not appropriate for the study
Read by machine on 9 November 2026.
Where in South Korea
- Inha University HospitalIncheon, South KoreaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- Inha University Hospital
- Trial code
- NCT07856472
- Record updated
- 2 October 2026
- Original description
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.Read full original descriptionShow less
Research for the Development and Clinical Application of Artificial Intelligence-powered Electrocardiography for Diagnosis and Prognostic Prediction in Cardiovascular Disease (AI-CVD): Multicenter Retrospective Study
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.
Inclusion: Patients aged 18 years or older diagnosed with cardiovascular diseases, including coronary artery disease and heart failure; Patients with 12-lead electrocardiogram (ECG) records extractable as text (XML.
Exclusion: Patients deemed inappropriate as study subjects by the investigator's judgment.