Machine learning validation of the AVAS classification compared to ultrasound mapping in a multicentre study

Machine learning validation of the AVAS classification compared to ultrasound mapping in a multicentre study

Abstract The Arteriovenous Access Stage (AVAS) classification simplifies information about suitability of vessels for vascular access (VA). It’s been previously validated in a clinical study. Here, AVAS performance was tested against multiple ultrasound mapping measurements using machine learning. A...

Full description

Saved in:
Bibliographic Details
Main Authors: Katerina Lawrie, Petr Waldauf, Peter Balaz, Radoslav Bortel, Ricardo Lacerda, Emma Aitken, Krzysztof Letachowicz, Mario D’Oria, Vittorio Di Maso, Pavel Stasko, Antonio Gomes, Joana Fontainhas, Matej Pekar, Alena Srdelic, VAVASC Study Group, Stephen O’Neill
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Arteriovenous access
Classification system
Dialysis
Mapping
Random forest
Renal replacement therapy
Online Access:https://doi.org/10.1038/s41598-025-86456-3
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-86456-3

Similar Items