Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting

Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting

Background Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision‐making but remain limited. We developed machine learning algorithms that predict 1‐year stroke or death following TFCAS. Methods and Results The VQ...

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Bibliographic Details
Main Authors: Ben Li, Naomi Eisenberg, Derek Beaton, Douglas S. Lee, Leen Al‐Omran, Duminda N. Wijeysundera, Mohamad A. Hussain, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Graham Roche‐Nagle, Mohammed Al‐Omran
Format: Article
Language:English
Published: Wiley 2024-09-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
death
machine learning
prediction
stroke
transfemoral carotid artery stenting
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.124.035425

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.124.035425

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