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

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

Description

Eligibility

Age range

Not specified

Sex

All

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

Location