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Prediction of Outcome in the Vegetative State by Machine Learning Algorithms: A Model for Clinicians?
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Journal of Software Engineering and Applications·Volume 04 (2011)·Pages 388–390·Published 30 June 2011·DOI10.4236/jsea.2011.46044
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Abstract
Purpose of this study was to compare different Machine Learning classifiers (C4.5, Support Vector Machine, Naive Bayes, K-NN) in the early prediction of outcome of the subjects in vegetative state due to traumatic brain injury. Accuracy proved acceptable for all compared methods (AUC > 0.8), but sensitivity and specificity varied considerably and only some classifiers (in particular, Support Vector Machine) appear applicable models in the clinical routine. A combined use of classifiers is advisable.
KeywordsArtificial IntelligenceVegetative StateClinical OutcomePrognosis
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