The main goal of this project is to see if RADAR (Rapid AI-assisted Detection and Analysis of Rheumatic heart disease), which is a machine and deep-learning AI model, can help make rheumatic heart disease (RHD) screening easier to expand. Specifically, the project will test whether RADAR can screen as accurately-or more accurately-than current methods, and whether it can be used effectively in different low-resource settings. The aim is to show that RADAR could be adopted and used widely around the world.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
62
Continue standard of care with AI-assisted echocardiography
Uganda Heart Institute
Kampala, Uganda
Accuracy of Provider RHD Screening
The number of correctly identified (positive or negative) screenings divided by the total number of exams.
Time frame: 1 year
Interpretation Sensitivity
The number of correctly identified positive screening exams divided by the sum of correctly identified positive and incorrectly identified negative exams.
Time frame: 6 months
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