×
  • Select the area you would like to search.
  • ACTIVE INVESTIGATIONS Search for current projects using the investigator's name, institution, or keywords.
  • EXPERTS KNOWLEDGE BASE Enter keywords to search a list of questions and answers received and processed by the ADNI team.
  • ADNI PDFS Search any ADNI publication pdf by author, keyword, or PMID. Use an asterisk only to view all pdfs.
Filter results by:

3740 Total Publications

Disease progression model in subjects with mild cognitive impairment from the Alzheimer’s disease neuroimaging initiative: CSF biomarkers predict population subtypes.
Samtani, M. N., Raghavan, N., Shi, Y., Novak, G., Farnum, M., Lobanov, V., … Narayan, V. a.
2013; Journal British Journal of Clinical Pharmacology; vol. 75; no. 1; pp. 146-161; doi:10.1111/j.1365-2125.2012.04308.x
Prediction of Alzheimer’s disease and mild cognitive impairment using cortical morphological patterns.
Wee, C.-Y., Yap, P.-T., & Shen, D.
2013; Journal Human Brain Mapping; vol. 34; no. 12; pp. 3411-3425; doi:10.1002/hbm.22156
Critical ages in the life course of the adult brain: nonlinear subcortical aging.
Fjell, A. M., Westlye, L. T., Grydeland, H., Amlien, I., Espeseth, T., Reinvang, I., … Walhovd, K. B.
2013; Journal Neurobiology of Aging; vol. 34; no. 10; pp. 2239-47; doi:10.1016/j.neurobiolaging.2013.04.006
Advanced Psychometric Analysis and the Alzheimer's Disease Neuroimaging Initiative: Reports from the 2011 Friday Harbor Conference
Dan Mungas,1 Paul K. Crane,2 Laura E. Gibbons,2 Jennifer J. Manly,3 M. Maria Glymour,4 and Richard N. Jones5
PMID: 23232798 ; PMCID:3532555 ; 2013; Journal Brain Imaging Behavior; vol. 6; no. 4; pp. 485–488; doi:10.1007/s11682-012-9211-2
Alzheimer’s Disease Risk Assessment Using Large-Scale Machine Learning Methods
Casanova, R., Hsu, F.-C., Sink, K. M., Rapp, S. R., Williamson, J. D., Resnick, S. M., & Espeland, M. a.
PMID: 24250789 ; PMCID:3826736 ; 2013; Journal PloS One; vol. 8; pp. e77949; doi:10.1371/journal.pone.0077949
GWAS of Cerebrospinal Fluid Tau Levels Identifies Risk Variants for Alzheimer’s Disease
Cruchaga, C., Kauwe, J. S. K., Harari, O., Jin, S. C., Cai, Y., Karch, C. M., … Goate, A. M.
PMID: 23562540 ; PMCID:3664945 ; 2013; Journal Neuron; vol. 78; no. 2; pp. 256-68; doi:10.1016/j.neuron.2013.02.026
Consistent 4D Brain Extraction of Serial Brain MR Images
Wang Y1, Li G2, Nie J2, Yap PT2, Guo L3, Shen D2.
PMID: 25089172 ; PMCID:4116794 ; 2013; Journal Proc SPIE Int Soc Opt Eng; doi:10.1117/12.2006651
Brain development and aging: Overlapping and unique patterns of change.
Tamnes, C. K., Walhovd, K. B., Dale, A. M., Østby, Y., Grydeland, H., Richardson, G., … Fjell, A. M.
2013; Journal Neuroimage; vol. 68; no. 2013; pp. 63-74; doi:10.1016/j.neuroimage.2012.11.039
Glucose metabolism during resting state reveals abnormal brain networks organization in the Alzheimer’s disease and mild cognitive impairment.
Sanabria-Diaz, G., Martinez-Montes, E., Melie-Garcia, L., & Alzheimer’s Disease Neuroimaging, I.
2013; Journal PloS One; vol. 8; no. 7; pp. e68860; doi:10.1371/journal.pone.0068860