Efficacy of AI EF Screening by Using Smartphone Application Recorded PLAX View Cardiac Ultrasound Video Clips
NCT06330103 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 923
Last updated 2024-03-26
Summary
Assessing the Efficacy of Artificial Intelligence in Left Ventricular Function Screening Using Parasternal Long Axis View Cardiac Ultrasound Video Clips
ABSTRACT BACKGROUND: Echocardiography serves as a fundamental diagnostic procedure for managing heart failure patients. Data from Thailand's Ministry of Public Health reveals that there is a substantial patient population, with over 100,000 admissions annually due to this condition. Nevertheless, the widespread implementation of echocardiography in this patient group remains challenging, primarily due to limitations in specialist resources, particularly in rural community hospitals. Although modern community hospitals are equipped with ultrasound machines capable of basic cardiac assessment (e.g., parasternal long axis view), the demand for expert cardiologists remains a formidable obstacle to achieving comprehensive diagnostic capabilities. Leveraging the capabilities of Artificial Intelligence (AI) technology, proficient in the accurate prediction and processing of diverse healthcare data types, offers a promising for addressing this prevailing issue. This study is designed to assess the effectiveness of AI in evaluating cardiac performance from parasternal long axis view ultrasound video clips obtained via the smartphone application.
OBJECTIVES: To evaluate the effectiveness of artificial intelligence in screening cardiac function from parasternal long axis view cardiac ultrasound video clips obtained through the smartphone application.
Conditions
- Heart Failure
- Heart Failure With Reduced Ejection Fraction
- Cardiac Failure
- Echocardiography
- Artificial Intelligence
Interventions
- OTHER
-
Easy EF
AI was integrated into the application smartphone and used smartphone camera to recorded shot VDO clip of heart ultrasound in parasternal long axis view and returned cardiac function result to user.
Sponsors & Collaborators
-
Chulalongkorn University
collaborator OTHER -
Rayong Hospital
lead OTHER
Study Design
- Allocation
- NON_RANDOMIZED
- Purpose
- DIAGNOSTIC
- Masking
- SINGLE
- Model
- PARALLEL
Eligibility
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2023-05-01
- Primary Completion
- 2023-07-31
- Completion
- 2023-07-31
Countries
- Thailand
Study Locations
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