AI-assisted detection of high-pitched bruits in arteriovenous fistulas using a digital stethoscope
The integration of this deep learning tool into clinical workflows could provide clinicians with a sensitive, objective, and time-efficient method for detecting high-pitched bruits which may be used in combination with other clinical signs for the detection of AVF complications such as stenosis. Implemented through a low-cost phono angiography protocol requiring minimal training, this approach has the potential to support earlier interventions and improve outcomes in the hemodialysis population.
Authors
- Austin Vas
- Francesco Bellocchio
- Jasmine Ion Titapiccolo (ORCID: https://orcid.org/0000-0001-5514-8182)
- Max Botler
- Ricardo Peralta (ORCID: https://orcid.org/0000-0001-6962-1073)
- Khaled Kahouli (ORCID: https://orcid.org/0009-0002-5702-0021)
- Felix Brockherde
- Luca Neri
- Nathan Warren
- The Arterio-Venous Fistula Bruit Electronic Auscultation for Monitoring (AVF-BEAM) Group
Institutions
- Fresenius Medical Care (United States) (US)
- Fresenius Medical Care Portugal (Portugal)
- Fresenius Medical Care (Germany) (DE)
Publication Details
- Journal
- The Journal of Vascular Access
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1177/11297298251396199
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00