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1800 Total Publications

Early detection of Alzheimer's disease using MRI hippocampal texture.
L. Sorensen, C. Igel, N. Liv Hansen, M. Osler, M. Lauritzen, E. Rostrup, M. Nielsen, I. Alzheimer's Disease Neuroimaging, B. the Australian Imaging and A. Lifestyle Flagship Study of
PMID: 26686837 ; 2015; Journal Hum Brain Mapp; vol. 37; no. 3; pp. 1148-61; AWTYFhFidzjauPDbjhkh doi:10.1002/hbm.23091
Corpus Callosum Atrophy Rate in Mild Cognitive Impairment and Prodromal Alzheimer’s Disease
Elahi, S., Bachman, A. H., Lee, S. H., Sidtis, J. J., & Ardekani, B. A.
PMID: 25633676 ; PMCID:4451933 ; 2015; Journal Journal of Alzheimer's Disease; vol. 45; no. 3; pp. 921-31; AWTYFhFidzjauPDbjhks doi:10.3233/JAD-142631
Exploring Multifractal-Based Features for Mild Alzheimer’s Disease Classification
Ni, H., Zhou, L., Ning, X., & Wang, L.
PMID: 26193379 ; 2015; Journal Magnetics Resonance in Medicine; vol. 76; no. 1; pp. 259-69; AWTYFhFidzjauPDbjhk5 doi:10.1002/mrm.25853
A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI
Iglesias, J. E., Augustinack, J. C., Nguyen, K., Player, C. M., Player, A., Wright, M., … Van Leemput, K.
PMID: 25936807 ; PMCID:4461537 ; 2015; Journal Neuroimage; vol. 115; pp. 117-137; AWTYJDUyMOwVf_qbJr5W doi:10.1016/j.neuroimage.2015.04.042
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
Brain Amyloid-􏰀 Burden Is Associated with Disruption of Intrinsic Functional Connectivity within the Medial Temporal Lobe in Cognitively Normal Elderly
Song Z1, Insel PS2, Buckley S2, Yohannes S3, Mezher A2, Simonson A2, Wilkins S4, Tosun D2, Mueller S2, Kramer JH4, Miller BL4, Weiner MW5.
PMID: 25698758 ; PMCID:4331637 ; 2015; Journal J Neurosci; vol. 35; no. 7; pp. 3240-7; AWTYmIlBwAl_G9zjEveA doi:10.1523/JNEUROSCI.2092-14.2015
Round robin test on quantification of amyloid-β 1–42 in cerebrospinal fluid by mass spectrometry
J. Pannee, J. Gobom, L. M. Shaw, M. Korecka, E. E. Chambers, M. Lame, R. Jenkins, W. Mylott, M. C. Carrillo, I. Zegers, H. Zetterberg, K. Blennow and E. Portelius
PMID: 26206625 ; 2015; Journal Alzheimers Dement; vol. 12; no. 1; pp. 55-9; AWTYk_61wAl_G9zjEvdU doi:10.1016/j.jalz.2015.06.1890
Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer’s disease: a machine learning approach.
Salvatore C, Cerasa A, Battista P, et al.
2015; Journal Frontiers in Neuroscience; AWUVLgpedzjauPDbjhrr
New scoring methodology improves the sensitivity of the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials.
Verma N, Beretvas SN, Pascual B, Masdeu JC, Markey MK.
2015; Journal Alzheimer's Research and Therapy; vol. 7; no. 1; pp. 64; AWUVLgpedzjauPDbjhsA
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