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3740 Total Publications

Multivariate Analysis of Structural MRI and PET (FDG and 18F- AV-45) for Alzheimer’s Disease and Its Prodromal Stages
Zhou Q, Goryawala M, Cabrerizo M, Barker W, Loewenstein D, Duara R, Adjouadi M
PMID: 25570142 ; 2014; Journal Conf Proc IEEE Eng Med Biol Soc; vol. 2014; pp. 1051-4; doi:10.1109/EMBC.2014.6943774
Identifying cost-effective predictive rules of amyloid-β level by integrating neuropsychological tests and plasma-based markers. J
Haghighi, M., Smith, A., Morgan, D., Small, B., & Huang, S.
2014; Journal Journal of Alzheimer's Disease; vol. 43; no. 4; pp. 1261-1270; doi:10.3233/JAD-140705
Genetic variation modifies risk for neurodegeneration based on biomarker status.
Hohman, T. J., Koran, M. E. I., & Thornton-Wells, T. A
2014; Journal Frontiers in Aging Neuroscience; vol. 6; pp. 183; doi:10.3389/fnagi.2014.00183
A Bayesian Nonparametric Regression Model With Normalized Weights: A Study of Hippocampal Atrophy in Alzheimer’s Disease.
Antoniano-Villalobos, I., Wade, S., & Walker, S. G.
2014; Journal Journal of the American Statistical Association; vol. 109; no. 506; pp. 477-490; doi:10.1080/01621459.2013.879061
Cholinergic basal forebrain atrophy predicts amyloid burden in Alzheimer’s disease
Stefan Teipel, Helmut Heinsen, Edson Amaro, Jr., Lea T. Grinberg, Bernd Krause, and Michel Grothe, for the Alzheimer’s Disease Neuroimaging Initiative.
PMID: 24176625 ; PMCID:4120959 ; 2014; Journal Neurobiology of Aging; vol. 35; no. 3; pp. 482-491; doi:10.1016/j.neurobiolaging.2013.09.029
Multiple instance learning for classification of dementia in brain MRI
Tong, T., Wolz, R., Gao, Q., Guerrero, R., Hajnal, J. V, & Rueckert, D.
PMID: 24858570 ; 2014; Journal Medical Image Analysis; vol. 18; no. 5; pp. 808-818; doi:10.1016/j.media.2014.04.006
Comparison of neuroimaging modalities for the prediction of conversion from mild cognitive impairment to Alzheimer’s dementia
Trzepacz, P. T., Yu, P., Sun, J., Schuh, K., Case, M., Witte, M. M., … Hake, A.
PMID: 23954175 ; 2014; Journal Neurobiology of Aging; vol. 35; no. 1; pp. 143-151; doi:10.1016/j.neurobiolaging.2013.06.018
Gaussian Mixture Models and Model Selection for [18F] Fluorodeoxyglucose Positron Emission Tomography Classification in Alzheimer’s Disease
Li, R., Perneczky, R., Yakushev, I., Förster, S., Kurz, A., Drzezga, A., & Kramer, S.
PMID: 25919662 ; PMCID:4412726 ; 2014; Journal PloS One; vol. 10; no. 4; pp. e0122731; doi:10.1371/journal.pone.0122731