Efficacy of AI EF Screening by Using Smartphone Application Recorded PLAX

Status Completed

Clinical Trial 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.

Clinical Trial Description

METHODS: The investigators built the smartphone application to collect parasternal long axis view video clips and used artificial intelligence "Easy EF" to evaluate cardiac function. All samples that were evaluated for LVEF by certified cardiologists, 70% of all clips were used to train AI, while the remaining 30% of clips were used to test if AI could process the results correctly. Artificial intelligence aims to classify cardiac function into three groups: Reduced EF, Mildly Reduced EF, and Preserved LV. ;

Study Design

Related Conditions & MeSH terms

Artificial Intelligence
Cardiac Failure
Echocardiography
Heart Failure
Heart Failure With Reduced Ejection Fraction

Clinical Trial Details

NCT number	NCT06330103
Study type	Interventional
Source	Rayong Hospital
Contact
Status	Completed
Phase	N/A
Start date	May 1, 2023
Completion date	July 31, 2023

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Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.

Phase 1: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

Efficacy of AI EF Screening by Using Smartphone Application Recorded PLAX View Cardiac Ultrasound Video Clips

Clinical Trial Summary

Clinical Trial Description

Study Design

Related Conditions & MeSH terms