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F. Moser, G. E. Rong and E. Martin, “Joint Cluster Analysis of Attribute and Relationship Data without Apriori Specification of the Number of Clusters,” In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, 12-15 August 2007.

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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.