FindTrial
Sign In

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

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

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0008388
Enrollment
15000
Registered
2023-04-27
Start date
2023-04-17
Completion date
Unknown
Last updated
2023-12-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

None listed

Sponsors

Inha University Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

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

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.

Design outcomes

Primary

MeasureTime frame
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

MeasureTime frame
Development of additional algorithms for application to clinical trials related to heart disease—

Countries

Korea, Republic of

Contacts

Public ContactHyo Bin Shin

Inha University Hospital

hbshin882@naver.com+82-2-890-2461

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026