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1800 Total Publications

integrative analysis of multi-dimensional imaging genomics data for alzheimers disease prediction
Zhang, Z., Huang, H., & Shen, D.
PMID: 25368574 ; PMCID:4201101 ; 2014; Journal Frontiers in Aging Neuroscience; vol. 6; pp. 260; AWTYs7amwAl_G9zjEvfe doi:10.3389/fnagi.2014.00260
Subclass-based multi-task learning for Alzheimer’s disease diagnosis
Suk, H.-I., Lee, S.-W., & Shen, D.
PMID: 25147522 ; PMCID:4124798 ; 2014; Journal Frontiers in Aging Neuroscience; vol. 6; pp. 168; AWTYmIlBwAl_G9zjEveL doi:10.3389/fnagi.2014.00168
Clustering-Induced Multi-task Learning for AD/MCI Classification
Suk, H.-I., & Shen, D.
PMID: 25320824 ; PMCID:4467456 ; 2014; Journal Medical Image Computing and Computer-Assisted Intervention; vol. 17; no. 3; pp. 393-400; AWTYmIlBwAl_G9zjEveM doi:10.1007/978-3-319-10443-0_50
Anxiety Symptoms in Amnestic Mild Cognitive Impairment Are Associated with Medial Temporal Atrophy and Predict Conversion to Alzheimer Disease
Mah, L., Binns, M. a, & Steffens, D. C
PMID: 25500120 ; 2014; Journal American Journal of Geriatric Psychiatry; vol. 23; no. 5; pp. 1-11; AWTYNIDFwAl_G9zjEvbG doi:10.1016/j.jagp.2014.10.005
Alterations in brain leptin signalling in spite of unchanged CSF leptin levels in Alzheimer’s disease
Maioli, S., Lodeiro, M., Merino-Serrais, P., Falahati, F., Khan, W., Puerta, E., … Cedazo-Minguez, A.
PMID: 25453257 ; 2014; Journal Aging Cell; vol. 3; pp. 1-8; AWTYNIDFwAl_G9zjEvbH doi:10.1111/acel.12281
Everyday Cognition scale items that best discriminate between and predict progression from clinically normal to mild cognitive impairment
Marshall, G. A., Zoller, A. S., Kelly, K. E., Amariglio, R. E., Locascio, J. J., Johnson, K. A., … For The Alzheimer’s Disease Neuroimaging Initiative.
PMID: 25274110 ; PMCID:4247808 ; 2014; Journal Current Alzheimer's Research; vol. 11; no. 9; pp. 853-61; AWTYNIDFwAl_G9zjEvbR doi:10.1016/j.biotechadv.2011.08.021.Secreted
Biomarkers for Predicting Cognitive Decline in those with Normal Cognition
Steenland, K., Zhao, L., Goldstein, F., Cellar, J., & Lah, J.
PMID: 24496071 ; PMCID:4462517 ; 2014; Journal Journal of Alzheimer's Disease; vol. 40; no. 3; pp. 587-594; AWTYmIlBwAl_G9zjEveF doi:10.3233/JAD-2014-131343
Automated template-based hippocampal segmentations from MRI: the effects of 1.5T or 3T field strength on accuracy.
Macdonald, K. E., Leung, K. K., Bartlett, J. W., Blair, M., Malone, I. B., Barnes, J., … Fox, N. C.
2014; Journal Neuroinformatics; vol. 12; no. 3; pp. 405-12; AWUVKtlhdzjauPDbjhrh doi:10.1007/s12021-013-9217-y
Manifold population modeling as a neuro-imaging biomarker: Application to ADNI and ADNI-GO
Guerrero, R., Wolz, R., Rao, a W., & Rueckert, D.
PMID: 24657351 ; 2014; Journal Neuroimage; vol. 94; pp. 275-86; AWTYG0yudzjauPDbjhlj doi:10.1016/j.neuroimage.2014.03.036
Evaluation of Whole Brain Health in Aging and Alzheimer’s Disease: A Standard Procedure for Scoring an MRI-Based Brain Atrophy and Lesion Index
Guo, H., Song, X., Schmidt, M. H., Vandorpe, R., Yang, Z., LeBlanc, E., … Rockwood, K.
PMID: 24927702 ; 2014; Journal Journal of Alzheimer's Disease; vol. 42; no. 2; pp. 691-703; AWTYG0yudzjauPDbjhlp doi:10.3233/JAD-140333