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R. W. Thatcher, R. A. Walker, C. J. Biver, D. M. North and R. Curtin, “Sensitivity and Specificity of an EEG Normative Database: Validation and Clinical Correlation,” Journal of Neurotherapy, Vol. 7, No. 3-4, 2003, pp. 87-121. doi:10.1300/J184v07n03_05

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• TITLE: Prediction of Outcome in the Vegetative State by Machine Learning Algorithms: A Model for Clinicians?

  AUTHORS: Loris Pignolo, Vincenzo i Lagan

  KEYWORDS: Artificial Intelligence, Vegetative State, Clinical Outcome, Prognosis

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.4 No.6, July 1, 2011

  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.