Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models

Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models

Background and Purpose: Stroke-related functional risk scores are used to predict patients' functional outcomes following a stroke event. We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular tr...

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Bibliographic Details
Main Authors: Shakiru A. Alaka, Bijoy K. Menon, Anita Brobbey, Tyler Williamson, Mayank Goyal, Andrew M. Demchuk, Michael D. Hill, Tolulope T. Sajobi
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-08-01
Series:Frontiers in Neurology
Subjects:
machine learning
acute ischemic stroke
functional outcome
clinical risk prediction
discrimination calibration
Online Access:https://www.frontiersin.org/article/10.3389/fneur.2020.00889/full

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https://www.frontiersin.org/article/10.3389/fneur.2020.00889/full

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