Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair

Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair

Background Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EVAR) are complex procedures that carry a significant risk of complications. While risk prediction tools can aid in clinical decision making, they remain limited. We developed machine learning algorithms...

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Bibliographic Details
Main Authors: Ben Li, Naomi Eisenberg, Derek Beaton, Douglas S. Lee, Badr Aljabri, Leen Al‐Omran, Duminda N. Wijeysundera, Ori D. Rotstein, Thomas F. Lindsay, Charles de Mestral, Muhammad Mamdani, Graham Roche‐Nagle, Mohammed Al‐Omran
Format: Article
Language:English
Published: Wiley 2025-03-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
complex endovascular aneurysm repair (EVAR)
machine learning
outcome
prediction
thoracic endovascular aortic repair (TEVAR)
thoracoabdominal aortic aneurysm life‐altering event (TALE)
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.124.039221
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https://www.ahajournals.org/doi/10.1161/JAHA.124.039221

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