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1736 Total Publications

Equivalence of kernel machine regression and kernel distance covariance for multidimensional phenotype association studies
Wen-Yu Hua, Debashis Ghosh.
2015; Journal Biometrics; vol. 71; no. 3; pp. 812-820;
Prediction of brain age suggests accelerated atrophy after traumatic brain injury.
Cole JH, Leech R, Sharp DJ, for the Alzheimer’s Disease Neuroimaging Initiative.
2015; Journal Annals of Neurology; vol. 77; no. 4; pp. 571-581; doi:10.1002/ana.24367.
Does posterior cingulate hypometabolism result from disconnection or local pathology across preclinical and clinical stages of Alzheimer's disease?
S. Teipel, M. J. Grothe and I. Alzheimer s Disease Neuroimaging
2015; Journal Eur J Nucl Med Mol Imaging; vol. 43; no. 3; pp. 526-36; doi:10.1007/s00259-015-3222-3
Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning
G. Wu, M. Kim, Q. Wang, B. C. Munsell and D. Shen
2015; Journal IEEE Trans Biomed Eng; vol. 63; no. 7; pp. 1505-16; doi:10.1109/TBME.2015.2496253
Pairwise Latent Semantic Association for Similarity Computation in Medical Imaging
F. Zhang, Y. Song, W. Cai, S. Liu, S. Liu, S. Pujol, R. Kikinis, Y. Xia, M. J. Fulham, D. D. Feng and I. Alzheimers Disease Neuroimaging
2015; Journal IEEE Trans Biomed Eng; vol. 63; no. 5; pp. 1058-1069; doi:10.1109/TBME.2015.2478028
The role of visualization and 3-D printing in biological data mining.
Weiss, T. L., Zieselman, A., Hill, D. P., Diamond, S. G., Shen, L., Saykin, A. J., & Moore, J. H.
2015; Journal BioData Mining; vol. 8; pp. 22; doi:10.1186/s13040-015-0056-2
Mapping CSF biomarker profiles onto NIA–AA guidelines for Alzheimer’s disease.
Alexopoulos P, Roesler J, Thierjung N, et al.
2015; Journal European Archives of Psychiatry and Clinical Neuroscience; pp. 1-11;
Manifold regularized multitask feature learning for multimodality disease classification.
Jie, B., Zhang, D., Cheng, B., & Shen, D.
2015; Journal Human Brain Mapping; vol. 36; no. 2; pp. 489-507; doi:10.1002/hbm.22642
An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer’s disease.
Schmitter, D., Roche, A., Maréchal, B., Ribes, D., Abdulkadir, A., Bach-Cuadra, M., … Krueger, G.
2015; Journal Neuroimage: Clinical; vol. 7; pp. 7-17; doi:10.1016/j.nicl.2014.11.001
Head-to-head comparison of two popular cortical thickness extraction algorithms: a cross-sectional and longitudinal study.
Redolfi, A., Manset, D., Barkhof, F., Wahlund, L.-O., Glatard, T., Mangin, J.-F., & Frisoni, G. B.
2015; Journal PloS One; vol. 10; no. 3; pp. e0117692; doi:10.1371/journal.pone.0117692