Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.

Abstract

The search for markers that are able to predict the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is crucial for early mechanistic therapies. Using artificial neural networks (ANNs), 22 variables that are known risk factors of AD were analyzed in 80 patients with aMCI, for a period spanning at least 2 years. The cases… (More)
DOI: 10.3233/JAD-2010-1300

Topics

Cite this paper

@article{Tabaton2010ArtificialNN, title={Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.}, author={Massimo Tabaton and Patrizio R Odetti and Sergio Cammarata and Roberta Borghi and Fiammetta Monacelli and Carlo Caltagirone and Paola Boss{\`u} and Massimo P Buscema and Enzo Grossi}, journal={Journal of Alzheimer's disease : JAD}, year={2010}, volume={19 3}, pages={1035-40} }