ADNI | Publications

Filter results by:

1800 Total Publications

Predicting Reduction of Cerebrospinal Fluid β-Amyloid 42 in Cognitively Healthy Controls.
Mattsson, N., Insel, P. S., Donohue, M., Jagust, W., Sperling, R., Aisen, P., & Weiner, M. W.
PMID: 25775167 ; 2015; Journal JAMA Neurology; vol. 72; no. 5; pp. 1-7; AWTYN5pfwAl_G9zjEvbf doi:10.1001/jamaneurol.2014.4530

Neuropsychological Testing Predicts Cerebrospinal Fluid Amyloid- in MildCognitive Impairment
Kandel, B. M., Avants, B. B., Gee, J. C., Arnold, S. E., & Wolk, D. A.
PMID: 25881908 ; PMCID:4699841 ; 2015; Journal Journal of Alzheimer's Disease; vol. 46; no. 4; pp. 901-12; AWTYJ1j0wAl_G9zjEvZ0 doi:10.3233/JAD-142943

The Alzheimer’s Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans
Kang, J.-H., Korecka, M., Figurski, M. J., Toledo, J. B., Blennow, K., Zetterberg, H., … Shaw, L. M.
PMID: 26194312 ; PMCID:5127404 ; 2015; Journal Alzheimer's and Dementia; vol. 11; no. 7; pp. 772-791; AWTYJ1j0wAl_G9zjEvZ2 doi:10.1016/j.jalz.2015.05.003

Feature Selection Based on the SVM Weight Vector for Classification of Dementia
Bron, E., Smits, M., Niessen, W., & Klein, S.
PMID: 25974958 ; 2015; Journal IEEE Journal of Biomedical and Health Informatics; vol. 19; no. 5; pp. 1617-1626; AWTX7HmYdzjauPDbjhjX doi:10.1109/JBHI.2015.2432832

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge
Bron, E. E., Smits, M., van der Flier, W. M., Vrenken, H., Barkhof, F., Scheltens, P., … Klein, S.
PMID: 25652394 ; PMCID:4943029 ; 2015; Journal Neuroimage; vol. 111; pp. 562-579; AWTX7HmYdzjauPDbjhjY doi:10.1016/j.neuroimage.2015.01.048

The Effect of Age Correction on Multivariate Classification in Alzheimer’s Disease, with a Focus on the Characteristics of Incorrectly and Correctly Classified Subjects
F. Falahati, D. Ferreira, H. Soininen, P. Mecocci, B. Vellas, M. Tsolaki, I. Kloszewska, S. Lovestone, M. Eriksdotter, L. O. Wahlund, A. Simmons, E. Westman, c. AddNeuroMed and I. the Alzheimer's Disease Neuroimaging
PMID: 26440606 ; PMCID:4754326 ; 2015; Journal Brain Topogr; vol. 29; no. 2; pp. 296-307; AWTYGAtkMOwVf_qbJr4W doi:10.1007/s10548-015-0455-1

Feature-ranking-based Alzheimer’s disease classification from structural MRI
I. Beheshti, Demirel and A. s. D. N. Initiative
PMID: 26657976 ; 2015; Journal Magnetic resonance imaging; vol. 34; no. 3; pp. 252-263; AWTYGAtkMOwVf_qbJr4b doi:10.1016/j.mri.2015.11.009

Quantitative validation of a visual rating scale for frontal atrophy: associations with clinical status, APOE e4, CSF biomarkers and cognition
D. Ferreira, L. Cavallin, T. Granberg, O. Lindberg, C. Aguilar, P. Mecocci, B. Vellas, M. Tsolaki, I. Kloszewska, H. Soininen, S. Lovestone, A. Simmons, L. O. Wahlund, E. Westman, c. AddNeuroMed and I. for the Alzheimer's Disease Neuroimaging
PMID: 26560730 ; 2015; Journal Eur Radiol; vol. 26; no. 8; pp. 2597-610; AWTYGAtkMOwVf_qbJr4h doi:10.1007/s00330-015-4101-9

A kernel machine method for detecting effects of interaction between multidimensional variable sets: An imaging genetics application
Ge, T., Nichols, T. E., Ghosh, D., Mormino, E. C., Smoller, J. W., & Sabuncu, M. R.
PMID: 25600633 ; PMCID:4339421 ; 2015; Journal Neuroimage; vol. 109; pp. 505-514; AWTYHKVzdzjauPDbjhlz doi:10.1016/j.neuroimage.2015.01.029

The Alzheimer’s Disease Neuroimaging Initiative phase 2: Increasing the length, breadth, and depth of our understanding
Beckett, L. A., Donohue, M. C., Wang, C., Aisen, P., Harvey, D. J., & Saito, N.
PMID: 26194315 ; PMCID:4510463 ; 2015; Journal Alzheimer's and Dementia; vol. 11; no. 7; pp. 823-31; AWTX5LQ2MOwVf_qbJr10 doi:10.1016/j.jalz.2015.05.004