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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...
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| 出版年: | PLoS One |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2015
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| 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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