Research for the Development and Clinical Application of Artificial Intelligence-powered Electr ocardiography for Diagnosis and Prognostic Prediction in Cardiovascular Disease (AI-CVD): Multi center retrospective study
Not Applicable
Recruiting
- Conditions
- Diseases of the circulatory system
- Registration Number
- KCT0008388
- Lead Sponsor
- Inha University Hospital
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 15000
Inclusion Criteria
ECG for patients over 18 years of age diagnosed with heart disease with an ECG record that can be extracted with text (XML) files.
Exclusion Criteria
This study is a data collection study using an electrocardiogram, and there are no exclusion criteria other than patients who are inappropriate as subjects by the judgment of the researcher.
Study & Design
- Study Type
- Observational Study
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method An artificial intelligence-based electrocardiogram prediction program developed using a 12-lead electrocardiogram deep learning algorithm extracts encrypted raw data of cardiovascular disease patients and verifies its validity
- Secondary Outcome Measures
Name Time Method Development of additional algorithms for application to clinical trials related to heart disease