Trials / Completed
CompletedNCT04996381
Feasibility of AI-based Heart Function Prediction Model Using CXR
Feasibility of Artificial Intelligence-based Heart Function Prediction Model Using Chest Radiography
- Status
- Completed
- Phase
- —
- Study type
- Observational
- Enrollment
- 505 (actual)
- Sponsor
- Yonsei University · Academic / Other
- Sex
- All
- Age
- 20 Years – 90 Years
- Healthy volunteers
- Not accepted
Summary
The investigators will develop an artificial intelligence model to predict left ventricular ejection fraction using chest radiographic images and transthoracic echocardiography data.
Detailed description
Echocardiography should be considered at an early stage in patients who have first developed heart failure or who do not have information about heart function, but the examination may be delayed due to lack of time and manpower in the actual medical field. Primary Objective: Use chest radiographs to predict the left ventricular ejection fraction
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DIAGNOSTIC_TEST | Scanning Chest X-rays and performing AI algorithms on images | Chest X-Rays; AI CNNs; Results |
Timeline
- Start date
- 2022-03-01
- Primary completion
- 2022-06-30
- Completion
- 2022-09-01
- First posted
- 2021-08-09
- Last updated
- 2022-09-14
Locations
1 site across 1 country: South Korea
Source: ClinicalTrials.gov record NCT04996381. Inclusion in this directory is not an endorsement.