Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy

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ID: 115344
2014
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Abstract
We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter datasets, likely further improving prediction. Finally, we propose that a robust machine learning system can potentially optimise the selection pro …
Reference Key
h2014plosmachine Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Asadi H;Dowling R;Yan B;Mitchell P;;
Journal PloS one
Year 2014
DOI
DOI not found
URL
https://www.ncbi.nlm.nih.gov/pubmed/24520356
Keywords
support vector machine neural networks Computer National Center for Biotechnology Information NCBI NLM MEDLINE humans pubmed abstract nih national institutes of health national library of medicine models treatment outcome adult female male aged theoretical roc curve artificial intelligence* pmid:24520356 pmc3919736 doi:10.1371/journal.pone.0088225 hamed asadi richard dowling peter mitchell brain ischemia / etiology* brain ischemia / therapy* endovascular procedures / adverse effects* intracranial hemorrhages / pathology stroke / etiology* stroke / therapy* Machine learning stroke artificial neural networks machine learning algorithms ischemic stroke hemorrhage infarction support vector machines

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