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1800 Total Publications

Multiple Effect of APOE Genotype on Clinical and Neuroimaging Biomarkers Across Alzheimer’s Disease Spectrum
Y. Liu, L. Tan, H. F. Wang, Y. Liu, X. K. Hao, C. C. Tan, T. Jiang, B. Liu, D. Q. Zhang, J. T. Yu and I. Alzheimer's Disease Neuroimaging
PMID: 26298664 ; 2015; Journal Mol Neurobiol; vol. 53; no. 7; pp. 4539-47; AWTYO_KSMOwVf_qbJr6d doi:10.1007/s12035-015-9388-7
Optimizing Regions-of-Interest Composites for Capturing Treatment Effects on Brain Amyloid in Clinical Trials.
Tryputsen, V., DiBernardo, A., Samtani, M., Novak, G. P., Narayan, V. A., & Raghavan, N.
PMID: 25114074 ; 2015; Journal Journal of Alzheimer's Disease; vol. 43; no. 3; pp. 809-821; AWTYmoe0dzjauPDbjhou doi:10.3233/JAD-131979
A novel cortical thickness estimation method based on volumetric Laplace–Beltrami operator and heat kernel
Wang, G., Zhang, X., Su, Q., Shi, J., Caselli, R. J., & Wang, Y.
PMID: 25700360 ; PMCID:4405465 ; 2015; Journal Medical Image Analysis; vol. 22; no. 1; pp. 1-20; AWTYnnPpwAl_G9zjEvet doi:10.1016/j.media.2015.01.005
The neural correlates of anomia in the conversion from mild cognitive impairment to Alzheimer's disease
E. Pravata, J. Tavernier, R. Parker, H. Vavro, J. E. Mintzer and M. V. Spampinato
2015; Journal Neuroradiology; vol. 58; no. 1; pp. 59-67; AWUVQIWPMOwVf_qbJr9w doi:10.1007/s00234-015-1596-3
Chronic Depressive Symptomatology in Mild Cognitive Impairment Is Associated with Frontal Atrophy Rate which Hastens Conversion to Alzheimer Dementia
S. Sacuiu, P. S. Insel, S. Mueller, D. Tosun, N. Mattsson, C. R. Jack, Jr., C. DeCarli, R. Petersen, P. S. Aisen, M. W. Weiner, R. S. Mackin and I. Alzheimer's Disease Neuroimaging
2015; Journal Am J Geriatr Psychiatry; vol. 24; no. 2; pp. 126-35; AWUVQIWPMOwVf_qbJr9x doi:10.1016/j.jagp.2015.03.006
Comprehensive gene- and pathway-based analysis of depressive symptoms in older adults.
Nho, K., Ramanan, V. K., Horgusluoglu, E., Kim, S., Inlow, M. H., Risacher, S. L., … Saykin, A. J.
2015; Journal Journal of Alzheimer's Disease; vol. 45; no. 4; pp. 1197-1206; AWUVOl88MOwVf_qbJr9e doi:10.3233/JAD-148009
Structural imaging biomarkers of Alzheimer’s disease: predicting disease progression.
Eskildsen, S. F., Coupé, P., Fonov, V. S., Pruessner, J. C., & Collins, D. L
2015; Journal Neurobiology of Aging; vol. 36; pp. S23-S31; AWUVOl88MOwVf_qbJr9h doi:10.1016/j.neurobiolaging.2014.04.034
BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER’S DISEASE.
Eunjee Lee, Hongtu Zhu, Dehan Kong, Yalin Wang, Kelly Sullivan Giovanello, and Joseph G Ibrahim, for the Alzheimer’s Disease Neuroimaging Initiative.
2015; Journal Annals of Applied Statistics; vol. 9; no. 4; pp. 2153-2178; AWUVLgpedzjauPDbjhsD
Amyloid Beta-Weighted Cortical Thickness: A New Imaging Biomarker in Alzheimer’s Disease.
Mi Kim C, Hwang J, Lee J-M, et al.
2015; Journal Current Alzheimer's Research; AWUVLgpedzjauPDbjhsF
Partial Least Squares Correspondence Analysis: A Framework to Simultaneously Analyze Behavioral and Genetic Data
Beaton D, Dunlop J, Abdi H, for the Alzheimer’s Disease Neuroimaging I.
PMID: 26690774 ; 2015; Journal Psychological Medicine; vol. 21; no. 4; pp. 621-651; AWTX5LQ2MOwVf_qbJr1y doi:10.1037/met0000053