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RECRUITING
NCT02932176

Machine Learning for Handheld Vascular Studies

Sponsor: Duke University

View on ClinicalTrials.gov

Summary

The use of handheld arterial 'stethoscopes' (continuous wave Doppler devices) are ubiquitous in clinical practice. However, most users have received no formal training in their use or the interpretation of the returned data. This leads to delays in diagnosis and errors in diagnosis. The investigators intend to create a novel machine-learning algorithm to assist clinicians in the use of this data. This study will allow the investigators to collect sound files from the use of the devices and compare the algorithms output to established, existing vascular testing. There will be no invasive procedures, and use of these stethoscopes is part of routine clinical care. If successful, this data and algorithm will be later deployed via smartphone app for point of case testing in a separate study

Official title: Development and Validation of a Novel Machine-learning Algorithm to Assist in Handheld Vascular Diagnostics

Key Details

Gender

All

Age Range

Any - Any

Study Type

OBSERVATIONAL

Enrollment

180

Start Date

2016-09-07

Completion Date

2026-12-31

Last Updated

2026-03-05

Healthy Volunteers

Yes

Interventions

DEVICE

Non-invasive vascular testing

Results of clinically indicated non-invasive vascular testing will be used to develop a machine learning algorithm

DEVICE

machine-learning algorithm

Locations (1)

Duke University Medical Center

Durham, North Carolina, United States