Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.
about
Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individualsPolymorphisms in folate-metabolizing genes, chromosome damage, and risk of Down syndrome in Italian women: identification of key factors using artificial neural networks.Measurement of reaction time in the home for people with dementia: a feasibility studyStaging dementia from symptom profiles on a care partner website.Using artificial neural networks in clinical neuropsychology: high performance in mild cognitive impairment and Alzheimer's disease.Pregnancy risk factors in autism: a pilot study with artificial neural networks.Diagnosis of Alzheimer's Disease Using Dual-Tree Complex Wavelet Transform, PCA, and Feed-Forward Neural Network.Three-Dimensional Eigenbrain for the Detection of Subjects and Brain Regions Related with Alzheimer's Disease.
P2860
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P2860
Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.
description
2010 nî lūn-bûn
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2010年の論文
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2010年学术文章
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name
Artificial neural networks ide ...... tic mild cognitive impairment.
@en
Artificial neural networks ide ...... tic mild cognitive impairment.
@nl
type
label
Artificial neural networks ide ...... tic mild cognitive impairment.
@en
Artificial neural networks ide ...... tic mild cognitive impairment.
@nl
prefLabel
Artificial neural networks ide ...... tic mild cognitive impairment.
@en
Artificial neural networks ide ...... tic mild cognitive impairment.
@nl
P2093
P50
P356
P1476
Artificial neural networks ide ...... tic mild cognitive impairment.
@en
P2093
Enzo Grossi
Massimo Buscema
Massimo Tabaton
Paola Bossù
Roberta Borghi
Sergio Cammarata
P304
P356
10.3233/JAD-2010-1300
P577
2010-01-01T00:00:00Z