Machine Learning-Based Prediction of Brain Tissue Infarction in Patients With Acute Ischemic Stroke Treated With Theophylline as an Add-On to Thrombolytic Therapy: A Randomized Clinical Trial Subgroup Analysis

Machine Learning-Based Prediction of Brain Tissue Infarction in Patients With Acute Ischemic Stroke Treated With Theophylline as an Add-On to Thrombolytic Therapy: A Randomized Clinical Trial Subgroup Analysis

Background and Purpose: The theophylline in acute ischemic stroke trial investigated the neuroprotective effect of theophylline as an add-on to thrombolytic therapy in patients with acute ischemic stroke. The aim of this pre-planned subgroup analysis was to use predictive modeling to virtually test...

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Bibliographic Details
Main Authors: Boris Modrau, Anthony Winder, Niels Hjort, Martin Nygård Johansen, Grethe Andersen, Jens Fiehler, Henrik Vorum, Nils D. Forkert
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-05-01
Series:Frontiers in Neurology
Subjects:
stroke
thrombolytic therapy
clinical trial
theophylline
reperfusion
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2021.613029/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2021.613029/full

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