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Publications

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2110 Total Publications

Integrative genomics identifies APOE ε4 effectors in Alzheimer’s disease.
Rhinn, H., Fujita, R., Qiang, L., Cheng, R., Lee, J. H., & Abeliovich, A.
2013; Journal Nature; vol. 500; no. 7460; pp. 45-50; doi:10.1038/nature12415
Relationship between imaging biomarkers, age, progression and symptom severity in Alzheimer’s disease.
Dukart, J., Mueller, K., Villringer, A., Kherif, F., Draganski, B., Frackowiak, R., & Schroeter, M. L.
2013; Journal Neuroimage: Clinical; vol. 3; pp. 84-94; doi:10.1016/j.nicl.2013.07.005
Effects of baseline CSF alpha-synuclein on regional brain atrophy rates in healthy elders, mild cognitive impairment and Alzheimer’s disease.
Mattsson, N., Insel, P., Tosun, D., Zhang, J., Jack Jr., C. R., Galasko, D., … Weiner, M.
2013; Journal PloS One; vol. 8; no. 12; pp. e85443; doi:10.1371/journal.pone.0085443
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
Multi-atlas segmentation without registration: a supervoxel-based approach.
Wang, H., & Yushkevich, P. a.
2013; Journal Medical Image Computing and Computer-Assisted Intervention; vol. 16; no. 3; pp. 535-42; doi:10.1007/978-3-642-40760-4_67
Random forest-based similarity measures for multi-modal classification of Alzheimer’s disease.
Gray, K. R., Aljabar, P., Heckemann, R. a., Hammers, A., & Rueckert, D.
2013; Journal Neuroimage; vol. 65; pp. 167-175; doi:10.1016/j.neuroimage.2012.09.065
Modeling disease progression via multi-task learning.
Zhou, J., Liu, J., Narayan, V. a, & Ye, J.
2013; Journal Neuroimage; vol. 78; pp. 233-48; doi:10.1016/j.neuroimage.2013.03.073
Deformable templates guided discriminative models for robust 3D brain MRI segmentation.
Liu, C.-Y., Iglesias, J. E., & Tu, Z.
2013; Journal Neuroinformatics; vol. 11; no. 4; pp. 447-68; doi:10.1007/s12021-013-9190-5
Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers.
Shaffer, J. L., Petrella, J. R., Sheldon, F. C., Choudhury, K. R., Calhoun, V. D., Coleman, R. E., & Doraiswamy, P. M.
2013; Journal Radiology; vol. 266; no. 2; pp. 583-591; doi:10.1148/radiol.12120010
Longitudinal change in CSF Tau and Aβ biomarkers for up to 48 months in ADNI.
Toledo, J. B., Xie, S. X., Trojanowski, J. Q., & Shaw, L. M.
2013; Journal Acta Neuropathologica; vol. 126; no. 5; pp. 659-70; doi:10.1007/s00401-013-1151-4