The implicit function as squashing time model: a novel parallel nonlinear EEG analysis technique distinguishing mild cognitive impairment and Alzheimer's disease subjects with high degree of accuracy.
about
Polymorphisms in folate-metabolizing genes, chromosome damage, and risk of Down syndrome in Italian women: identification of key factors using artificial neural networks.Recognition of morphometric vertebral fractures by artificial neural networks: analysis from GISMO Lombardia Database.Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer's Disease and Mild Cognitive ImpairmentRole of XPC, XPD, XRCC1, GSTP genetic polymorphisms and Barrett's esophagus in a cohort of Italian subjects. A neural network analysis.Artificial Neural Networks for Early Prediction of Mortality in Patients with Non Variceal Upper GI Bleeding (UGIB)Evidence-based evaluation of diagnostic accuracy of resting EEG in dementia and mild cognitive impairment.
P2860
The implicit function as squashing time model: a novel parallel nonlinear EEG analysis technique distinguishing mild cognitive impairment and Alzheimer's disease subjects with high degree of accuracy.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
The implicit function as squas ...... with high degree of accuracy.
@en
type
label
The implicit function as squas ...... with high degree of accuracy.
@en
prefLabel
The implicit function as squas ...... with high degree of accuracy.
@en
P2093
P2860
P356
P1476
The implicit function as squas ...... with high degree of accuracy.
@en
P2093
Enzo Grossi
Francesca Bergami
Massimiliano Capriotti
Massimo Buscema
Paolo Rossini
P2860
P356
10.1155/2007/35021
P577
2007-01-01T00:00:00Z