1.
Effects of baseline CSF α-synuclein on regional brain atrophy rates in healthy elders, mild cognitive impairment and Alzheimer's disease.
by Mattsson, Niklas
PloS one, 2013, Vol.8(12), p.e85443
2.
Improved classification of Alzheimer's disease data via removal of nuisance variability.
by Koikkalainen, Juha
PloS one, 2012, Vol.7(2), p.e31112
3.
Vascular burden and Alzheimer disease pathologic progression
by Lo, Y., Raymond
Neurology, 2012, Vol.79(13), pp.1349-1355
4.
Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease
by Palmqvist, Sebastian
Neurology, 2015, Vol.85(14), p.1240-1249
5.
6.
Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease.
by Wolz, Robin
PloS one, 2011, Vol.6(10), p.e25446
7.
Brain structure and function as mediators of the effects of amyloid on memory.
by Mattsson, Niklas
Neurology, March 17, 2015, Vol.84(11), pp.1136-1144
8.
The role of vascular endothelial growth factor in neurodegeneration and cognitive decline: exploring interactions with biomarkers of Alzheimer disease.
by Hohman, Timothy J
JAMA neurology, May 2015, Vol.72(5), pp.520-529
9.
Memory, executive, and multidomain subtle cognitive impairment: clinical and biomarker findings.
by Toledo, Jon B
Neurology, July 14, 2015, Vol.85(2), pp.144-153
10.
Nonlinear Association Between Cerebrospinal Fluid and Florbetapir F-18 β-Amyloid Measures Across the Spectrum of Alzheimer Disease.
by Toledo, Jon B
JAMA neurology, May 2015, Vol.72(5), pp.571-581
11.
The mediational effects of FDG hypometabolism on the association between cerebrospinal fluid biomarkers and neurocognitive function.
by Dowling, N Maritza
NeuroImage, January 15, 2015, Vol.105, pp.357-368
12.
Subjective cognitive complaints contribute to misdiagnosis of mild cognitive impairment.
by Edmonds, Emily C
Journal of the International Neuropsychological Society : JINS, September 2014, Vol.20(8), pp.836-847
13.
The Alzheimer's Disease Assessment Scale-Cognitive-Plus (ADAS-Cog-Plus): an expansion of the ADAS-Cog to improve responsiveness in MCI.
by Skinner, Jeannine
Brain imaging and behavior, December 2012, Vol.6(4), pp.489-501
14.
Dysexecutive and amnesic AD subtypes defined by single indicator and modern psychometric approaches: relationships with SNPs in ADNI.
by Mukherjee, Shubhabrata
Brain imaging and behavior, December 2012, Vol.6(4), pp.649-660
15.
Semi-supervised multimodal relevance vector regression improves cognitive performance estimation from imaging and biological biomarkers.
by Cheng, Bo
Neuroinformatics, July 2013, Vol.11(3), pp.339-353
16.
Beta amyloid, tau, neuroimaging, and cognition: sequence modeling of biomarkers for Alzheimer's Disease.
by Han, S Duke
Brain imaging and behavior, December 2012, Vol.6(4), pp.610-620
17.
Estimating anatomical trajectories with Bayesian mixed-effects modeling.
by Ziegler, G
NeuroImage, November 1, 2015, Vol.121, pp.51-68
18.
Confirmatory factor analysis of the ADNI Neuropsychological Battery.
by Park, Lovingly Quitania
Brain imaging and behavior, December 2012, Vol.6(4), pp.528-539
19.
Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.
by Moradi, Elaheh
NeuroImage, January 1, 2015, Vol.104, pp.398-412
20.
Soluble BACE-1 Activity and sAβPPβ Concentrations in Alzheimer's Disease and Age-Matched Healthy Control Cerebrospinal Fluid from the Alzheimer's Disease Neuroimaging Initiative-1...
by Savage, Mary J
Journal of Alzheimer's disease : JAD, 2015, Vol.46(2), pp.431-440
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