Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction

Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction

Background and PurposeMechanical thrombectomy greatly improves stroke outcomes. Nonetheless, some patients fall short of full recovery despite good reperfusion. The purpose of this study was to develop machine learning (ML) models for the pre-interventional prediction of functional outcome at 3 mont...

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Bibliographic Details
Main Authors: Mohamed Sobhi Jabal, Olivier Joly, David Kallmes, George Harston, Alejandro Rabinstein, Thien Huynh, Waleed Brinjikji
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Neurology
Subjects:
ischemic stroke
artificial intelligence
machine learning
prognosis
prediction model
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2022.884693/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2022.884693/full

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