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Publications

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2110 Total Publications

Locally linear embedding (LLE) for MRI based Alzheimer’s disease classification.
Liu, X., Tosun, D., Weiner, M. W., & Schuff, N.
2013; Journal Neuroimage; vol. 83; pp. 148-57; doi:10.1016/j.neuroimage.2013.06.033

Predicting brain activity using a Bayesian spatial model.
Derado, G., Bowman, F. D., & Zhang, L.
2013; Journal Statistical Methods in Medical Research; vol. 22; no. 4; pp. 382-97; doi:10.1177/0962280212448972

Variance in Brain Volume with Advancing Age: Implications for Defining the Limits of Normality
David Alexander Dickie, Dominic E. Job, David Rodriguez Gonzalez, Susan D. Shenkin, Trevor S. Ahearn, Alison D. Murray, and Joanna M. Wardlaw.
2013; Journal PLoS One; vol. 8; no. 12; pp. e84093;

Clinical and multimodal biomarker correlates of ADNI neuropathological findings.
Toledo, J. B., Cairns, N. J., Da, X., Chen, K., Carter, D., Fleisher, A., … Trojanowski, J. Q.
2013; Journal Acta Neuropathologica Communications; vol. 1; no. 1; pp. 65; doi:10.1186/2051-5960-1-65

Identifying multi-analyte CSF biomarkers for Alzheimer’s disease in a multi-cohort study.
Leung YY, Toledo J, Nefedov A, et al.
2013; Journal Alzheimer's and Dementia; vol. 9; no. 4; pp. 128-9;

Frontolimbic atrophy is associated with agitation and aggression in mild cognitive impairment and Alzheimer’s disease.
Trzepacz, P. T., Yu, P., Bhamidipati, P. K., Willis, B., Forrester, T., Tabas, L., … Saykin, A. J.
2013; Journal Alzheimer's and Dementia; vol. 9; pp. 95-104; doi:10.1016/j.jalz.2012.10.005

Discriminative Feature Selection for Uncertain Graph Classification.
Kong X, Yu P, Wang X, Ragin A.
2013; Journal arXiv Prepr; vol. 2013; pp. 82-93;

Improved inference in Bayesian segmentation using Monte Carlo sampling: Application to hippocampal subfield volumetry.
Iglesias, J. E., Sabuncu, M. R., & Van Leemput, K.
2013; Journal Medical Image Analysis; vol. 17; no. 7; pp. 766-768; doi:10.1016/j.media.2013.04.005

White Matter Abnormalities and Structural Hippocampal Disconnections in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease.
Rowley, J., Fonov, V., Wu, O., Eskildsen, S. F., Schoemaker, D., Wu, L., … Rosa-Neto, P.
2013; Journal PloS One; vol. 8; no. 9; pp. 1-13; doi:10.1371/journal.pone.0074776

Meta-analysis based SVM classification enables accurate detection of Alzheimer’s disease across different clinical centers using FDG-PET and MRI.
Dukart, J., Mueller, K., Barthel, H., Villringer, A., Sabri, O., & Schroeter, M. L.
2013; Journal Psychiatry Research-Neuroimaging; vol. 212; no. 3; pp. 230-236; doi:10.1016/j.pscychresns.2012.04.007