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P. Domingos and M. Pazzani, “On the Optimality of the Simple Bayesian Classifier under Zero-One Loss,” Machine Learning, Vol. 29, 1997, pp. 103-137. doi:10.1023/A:1007413511361

has been cited by the following article:

• 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.