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3740 Total Publications

Improved longitudinal [18F]-AV45 amyloid PET by white matter reference and VOI-based partial volume effect correction
Brendel, M., Högenauer, M., Delker, A., Sauerbeck, J., Bartenstein, P., Seibyl, J., & Rominger, A.
PMID: 25482269 ; 2015; Journal Neuroimage; vol. 108; pp. 450-459; doi:10.1016/j.neuroimage.2014.11.055
Feature Selection Based on the SVM Weight Vector for Classification of Dementia
Bron, E., Smits, M., Niessen, W., & Klein, S.
PMID: 25974958 ; 2015; Journal IEEE Journal of Biomedical and Health Informatics; vol. 19; no. 5; pp. 1617-1626; doi:10.1109/JBHI.2015.2432832
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge
Bron, E. E., Smits, M., van der Flier, W. M., Vrenken, H., Barkhof, F., Scheltens, P., … Klein, S.
PMID: 25652394 ; PMCID:4943029 ; 2015; Journal Neuroimage; vol. 111; pp. 562-579; doi:10.1016/j.neuroimage.2015.01.048
Variations in the FRA10AC1 Fragile Site and 15q21 Are Associated with Cerebrospinal Fluid Aβ1-42 Level
Li, Q. S., Parrado, A. R., Samtani, M. N., & Narayan, V. A.
PMID: 26252872 ; PMCID:4529186 ; 2015; Journal PloS One; vol. 10; no. 8; pp. e0134000; doi:10.1371/journal.pone.0134000
Spatially Weighted Principal Component Analysis for Imaging Classification
Guo, R., Ahn, M., & Zhu, H.
PMID: 26089629 ; PMCID:4467033 ; 2015; Journal Journal of Computational and Graphical Statistics; vol. 24; no. 1; pp. 274-296; doi:10.1080/10618600.2014.912135
Development of a diagnostic test based on multiple continuous biomarkers with an imperfect reference test
L. Garcia Barrado, E. Coart and T. Burzykowski
PMID: 26388206 ; 2015; Journal Stat Med; vol. 35; no. 4; pp. 595-608; doi:10.1002/sim.6733
Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer’s disease: a machine learning approach.
Salvatore C, Cerasa A, Battista P, et al.
2015; Journal Frontiers in Neuroscience;
New scoring methodology improves the sensitivity of the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials.
Verma N, Beretvas SN, Pascual B, Masdeu JC, Markey MK.
2015; Journal Alzheimer's Research and Therapy; vol. 7; no. 1; pp. 64;
BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER’S DISEASE.
Eunjee Lee, Hongtu Zhu, Dehan Kong, Yalin Wang, Kelly Sullivan Giovanello, and Joseph G Ibrahim, for the Alzheimer’s Disease Neuroimaging Initiative.
2015; Journal Annals of Applied Statistics; vol. 9; no. 4; pp. 2153-2178;