protocolSection identificationModule nctId: NCT06330103, orgStudyIdInfo id: RayongH, briefTitle: Efficacy of AI EF Screening by Using Smartphone Application Recorded PLAX View Cardiac Ultrasound Video Clips, statusModule overallStatus: COMPLETED, startDateStruct date: 2023-05-01, primaryCompletionDateStruct date: 2023-07-31, completionDateStruct date: 2023-07-31, studyFirstPostDateStruct date: 2024-03-26, lastUpdatePostDateStruct date: 2024-03-26, sponsorCollaboratorsModule leadSponsor name: Rayong Hospital, class: OTHER, collaborators name: Chulalongkorn University, descriptionModule briefSummary: Assessing the Efficacy of Artificial Intelligence in Left Ventricular Function Screening Using Parasternal Long Axis View Cardiac Ultrasound Video ClipsABSTRACT 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., conditionsModule conditions: Heart Failure, conditions: Heart Failure With Reduced Ejection Fraction, conditions: Cardiac Failure, conditions: Echocardiography, conditions: Artificial Intelligence, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: NON_RANDOMIZED, interventionModel: PARALLEL, interventionModelDescription: 923 samples that were evaluated for LVEF by certified cardiologists, 739 clips were used to train AI, while the remaining 184 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., primaryPurpose: DIAGNOSTIC, maskingInfo masking: SINGLE, whoMasked: OUTCOMES_ASSESSOR, enrollmentInfo count: 923, type: ACTUAL, armsInterventionsModule interventions name: Easy EF, outcomesModule primaryOutcomes measure: efficiency of AI in screening left ventricular cardiac function by use smartphone application, eligibilityModule sex: ALL, stdAges: CHILD, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule locations facility: Rayong Hospital, city: Rayong, zip: 066, country: Thailand, geoPoint lat: 12.68095, lon: 101.25798, hasResults: False