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Publications

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2110 Total Publications

A Functional Varying-Coefficient Single-Index Model for Functional Response Data
J. Li, C. Huang and H. Zhu
PMID: 29200540 ; PMCID:5710774 ; 2017; Journal Journal of the American Statistical Association; vol. 112; no. 519; pp. 1169-1181; doi:10.1080/01621459.2016.1195742

Adaptive Testing of SNP-Brain Functional Connectivity Association via a Modular Network Analysis
C. Gao, J. Kim and W. Pan
PMID: 27896962 ; PMCID:5147491 ; 2017; Journal Pac Symp Biocomput; vol. 22; pp. 58-69;

Biomarkers and Functional Decline in Prodromal Alzheimer's Disease.
C. Robb, C. Udeh-Momoh, S. Wagenpfeil, J. Schope, P. Alexopoulos, R. Perneczky and I. Alzheimer's Disease Neuroimaging
PMID: 28372331 ; 2017; Journal J Alzheimers Dis; vol. 58; no. 1; pp. 69-78; doi:10.3233/JAD-161162

The prevalence and biomarkers’ characteristic of rapidly progressive Alzheimer’s disease from the Alzheimer’s Disease Neuroimaging Initiative database
M. Ba, X. Li, K. P. Ng, T. A. Pascoal, S. Mathotaarachchi, P. Rosa-Neto, S. Gauthier and I. Alzheimer's Disease Neuroimaging
PMID: 29067322 ; PMCID:5651370 ; 2017; Journal Alzheimers Dement (N Y); vol. 3; no. 1; pp. 107-113; doi:10.1016/j.trci.2016.12.005

Biomarkers and Functional Decline in Prodromal Alzheimer's Disease.
C. Robb, C. Udeh-Momoh, S. Wagenpfeil, J. Schope, P. Alexopoulos, R. Perneczky and I. Alzheimer's Disease Neuroimaging
PMID: 28372331 ; 2017; Journal J Alzheimers Dis; vol. 58; no. 1; pp. 69-78; doi:10.3233/JAD-161162

Autotaxin is Related to Metabolic Dysfunction and Predicts Alzheimer’s Disease Outcomes
K. E. McLimans, A. A. Willette and I. Alzheimer's Disease Neuroimaging
PMID: 27911319 ; PMCID:5654316 ; 2017; Journal J Alzheimers Dis; vol. 56; no. 1; pp. 403-413; doi:10.3233/JAD-160891

A Comparison of Accelerated and Non-accelerated MRI Scans for Brain Volume and Boundary Shift Integral Measures of Volume Change: Evidence from the ADNI Dataset
E. N. Manning, K. K. Leung, J. M. Nicholas, I. B. Malone, M. J. Cardoso, J. M. Schott, N. C. Fox, J. Barnes and I. Alzheimer's Disease Neuroimaging
PMCID:5443885 ; 2017; Journal Neuroinformatics; vol. 15; no. 2; pp. 215-226; doi:10.1007/s12021-017-9326-0

Deep ensemble learning of sparse regression models for brain disease diagnosis
H. I. Suk, S. W. Lee, D. Shen and I. Alzheimer's Disease Neuroimaging
PMCID:5808465 ; 2017; Journal Med Image Anal; vol. 37; pp. 101-113; doi:10.1016/j.media.2017.01.008

Ventricular and Periventricular Anomalies in the Aging and Cognitively Impaired Brain
K. L. Todd, T. Brighton, E. S. Norton, S. Schick, W. Elkins, O. Pletnikova, R. H. Fortinsky, J. C. Troncoso, P. J. Molfese, S. M. Resnick, J. C. Conover and I. Alzheimer's Disease Neuroimaging
PMCID:5771258 ; 2017; Journal Front Aging Neurosci; vol. 9; pp. 445; doi:10.3389/fnagi.2017.00445

Genome-wide association study identifies MAPT locus influencing human plasma tau levels
J. Chen, J. T. Yu, K. Wojta, H. F. Wang, H. Zetterberg, K. Blennow, J. S. Yokoyama, M. W. Weiner, J. H. Kramer, H. Rosen, B. L. Miller, G. Coppola, A. L. Boxer and I. Alzheimer's Disease Neuroimaging
PMID: 28100725 ; PMCID:5317386 ; 2017; Journal Neurology; vol. 88; no. 7; pp. 669-676; doi:10.1212/WNL.0000000000003615