Author(s)

Loris Pignolo, Vincenzo i Lagan

.

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.

Artificial Intelligence, Vegetative State, Clinical Outcome, Prognosis

L. Pignolo and V. Lagan, "Prediction of Outcome in the Vegetative State by Machine Learning Algorithms: A Model for Clinicians?," Journal of Software Engineering and Applications, Vol. 4 No. 6, 2011, pp. 388-390. doi: 10.4236/jsea.2011.46044.