Alzheimer’s Disease Neuroimaging Initiative

4453 Total Publications

Year	Title	Author	Journal
2015	Probability distribution function-based classification of structural MRI for the detection of Alzheimer’s disease	Beheshti, I., & Demirel, H.	Journal Computers in Biology and Medicine;
2015	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.	Journal Neuroimage;
2015	Feature Selection Based on the SVM Weight Vector for Classification of Dementia	Bron, E., Smits, M., Niessen, W., & Klein, S.	Journal IEEE Journal of Biomedical and Health Informatics;
2015	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.	Journal PloS One;
2015	Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE	Ayton, S., Faux, N. G., & Bush, A. I.	Journal Nature Communications;
2015	Alzheimer risk genes modulate the relationship between plasma apoE and cortical PiB binding	Lazaris A, Hwang KS, Goukasian N, Ramirez LM, Eastman J, Blanken AE, Teng E, Gylys K, Cole G, Saykin AJ, Shaw LM, Trojanowski JQ, Jagust WJ, Weiner MW, Apostolova LG,.	Journal Neurology: Genetics;
2015	Tract-Based Analysis of White Matter Degeneration in Alzheimer’s Disease	Lee, S.-H., Coutu, J.-P., Wilkens, P., Yendiki, A., Rosas, H. D., & Salat, D. H.	Journal Neuroscience;
2015	Identifying amyloid pathology–related cerebrospinal fluid biomarkers for Alzheimer’s disease in a multicohort study	Leung YY1, Toledo JB2, Nefedov A3, Polikar R4, Raghavan N5, Xie SX6, Farnum M7, Schultz T7, Baek Y2, Deerlin VV2, Hu WT8, Holtzman DM9, Fagan AM9, Perrin RJ10, Grossman M11, Soares HD12, Kling MA13, Mailman M7, Arnold SE14, Narayan VA7, Lee VM2, Shaw LM2, Baker D7, Wittenberg GM14, Trojanowski JQ2, Wang LS1	Journal Alzheimers Dementia;
2015	Antiphospholipid autoantibodies as blood biomarkers for detection of early stage Alzheimer’s disease	McIntyre, J. A., Ramsey, C. J., Gitter, B. D., Saykin, A. J., Wagenknecht, D. R., & Hyslop, P. A.	Journal Autoimmunity;
2015	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.	Journal Annals of Applied Statistics;