Residual brain function has been documented in vegetative state patients, yet early prognosis remains difficult. Purpose of this study was to identify by artificial Neural Network procedures the significant neurological signs correlated to, and predictive of outcome. The best networks test set accuracy was 70%, 72% and 70% for the entire patients' group and the posttraumatic and non-posttraumatic subgroups, respectively. The method accuracy does not reflect a perfect classification, but is significantly far from the random or educated guess and is in accordance with the results of previous clinical studies.
Pignolo, L., Riganello, F., Candelieri, A., Lagani, V. (2009). Vegetative state: Early prediction of clinical outcome by artificial neural network. In Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (July 4-5, 2009, Milan, Italy) (pp.91-96). Setubal : INSTICC - Institute Syst Technologies Information Control & Communication [10.5220/0002264300910096].
Vegetative state: Early prediction of clinical outcome by artificial neural network
Candelieri, A;
2009
Abstract
Residual brain function has been documented in vegetative state patients, yet early prognosis remains difficult. Purpose of this study was to identify by artificial Neural Network procedures the significant neurological signs correlated to, and predictive of outcome. The best networks test set accuracy was 70%, 72% and 70% for the entire patients' group and the posttraumatic and non-posttraumatic subgroups, respectively. The method accuracy does not reflect a perfect classification, but is significantly far from the random or educated guess and is in accordance with the results of previous clinical studies.
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