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Multiclass Support Vector Machine-Based Lesion Mapping Predicts Functional Outcome in Ischemic Stroke Patients

PURPOSE: The aim of this study was to investigate if ischemic stroke final infarction volume and location can be used to predict the associated functional outcome using a multi-class support vector machine (SVM). MATERIAL AND METHODS: Sixty-eight follow-up MR FLAIR datasets of ischemic stroke patien...

詳細記述

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書誌詳細
出版年:PLoS One
主要な著者: Forkert, Nils Daniel, Verleger, Tobias, Cheng, Bastian, Thomalla, Götz, Hilgetag, Claus C., Fiehler, Jens
フォーマット: Artigo
言語:Inglês
出版事項: Public Library of Science 2015
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC4476759/
https://ncbi.nlm.nih.gov/pubmed/26098418
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0129569
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