Vegetative state: Early prediction of clinical outcome by artificial neural network

L. Pignolo, F. Riganello, A. Candelieri, V. Lagani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

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.
Original languageEnglish (US)
Title of host publicationArtificial Neural Networks and Intelligent Information Processing - Proc. 5th Int. Workshop on Artificial Neural Networks and Intelligent Information Processing - ANNIIP 2009, held with ICINCO 2009
Pages91-96
Number of pages6
StatePublished - Dec 1 2009
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-23

Fingerprint

Dive into the research topics of 'Vegetative state: Early prediction of clinical outcome by artificial neural network'. Together they form a unique fingerprint.

Cite this