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This study generates robust clinical data to train ML/AI algorithms of the Sponsor's imPulse™ Una full-spectrum e-stethoscope for digital diagnostic feature synthesis of symptomatic SARS-CoV-2/COVID-19 biosignatures for rapid and accurate mass screening.
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This study is designed to evaluate the ability of the imPulse™ Una e-stethoscope to differentiate vibroacoustic signals in inpatients with and without confirmed COVID-19 as the first step to establish the performance characteristics - sensitivity, specificity, positive and negative predictive value - of the imPulse™ Una device for early and rapid, point-of-care diagnosis of COVID-19. This will inform the utility and design of further larger-scale studies using the device.
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34 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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