Feasibility of AI-based Heart Function Prediction Model Using CXR (AI-CXR)

Yonsei University

Status: Completed

Conditions: Chest X-ray for Clinical Evaluation

Treatments: Diagnostic Test: Scanning Chest X-rays and performing AI algorithms on images

Study type: Observational

Funder types: Other

Identifiers

NCT04996381

YonseiU

Details and patient eligibility

About

The investigators will develop an artificial intelligence model to predict left ventricular ejection fraction using chest radiographic images and transthoracic echocardiography data.

Full 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

Enrollment: 505 patients

Sex: All

Ages: 20 to 90 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Adults who are 20 years and older
• Patient who visited the emergency room or outpatient clinic due to dyspnea and chest pain

Exclusion criteria

• Patient refusal
• Uncertain radiographs or transthoracic echocardiography
• Uncertain tests results