Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy

ObjectiveTo investigate whether intracranial artery calcification (IAC) serves as a reliable imaging predictor of mechanical thrombectomy (MT) outcomes and to develop robust machine learning (ML) models incorporating preoperative emergency data to predict outcomes in patients with acute ischemic str...

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Bibliographic Details
Main Authors: Guangzong Li, Yuesen Zhang, Di Li, Manhong Zhao, Lin Yin
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Neurology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1642807/full
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