Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke

doi:10.1161/STROKEAHA.120.030092

Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	223-231
Number of pages	9
Journal	Stroke
Volume	52
Issue number	1
DOIs	https://doi.org/10.1161/STROKEAHA.120.030092
Publication status	Published - Jan 1 2021
Externally published	Yes

ASJC Scopus Subject Areas

Clinical Neurology
Cardiology and Cardiovascular Medicine
Advanced and Specialised Nursing

Keywords

acute ischemic stroke
computed tomographic perfusion
infarction
machine learning

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10.1161/STROKEAHA.120.030092

Cite this

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title = "Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke",

keywords = "acute ischemic stroke, computed tomographic perfusion, infarction, machine learning",

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language = "English",

volume = "52",

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journal = "Stroke",

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publisher = "Lippincott Williams and Wilkins",

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KW - computed tomographic perfusion

KW - infarction

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Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke

ASJC Scopus Subject Areas

Keywords

Access to Document

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