×
  • 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:

1800 Total Publications

Generalized fused group lasso regularized multi-task feature learning for predicting cognitive outcomes in Alzheimers Disease
P. Cao, X. Liu, H. Liu, J. Yang, D. Zhao, M. Huang and O. Zaiane
2018; Journal Computer Methods and Programs in Biomedicine; AWUW5A4cdzjauPDbjhuK
Progranulin levels in blood in Alzheimer's disease and mild cognitive impairment
Y. A. Cooper, D. Nachun, D. Dokuru, Z. Yang, A. M. Karydas, G. Serrero, B. Yue, A. L. Boxer, B. L. Miller and G. Coppola
PMCID:5945969 ; 2018; Journal Ann Clin Transl Neurol; vol. 5; no. 5; pp. 616-629; AWUW5A4cdzjauPDbjhuO doi:10.1002/acn3.560
18F-florbetapir Positron Emission Tomography-determined Cerebral beta-Amyloid Deposition and Neurocognitive Performance after Cardiac Surgery
R. Y. Klinger, O. G. James, S. Borges-Neto, T. Bisanar, Y. J. Li, W. Qi, M. Berger, N. Terrando, M. F. Newman, P. M. Doraiswamy and J. P. Mathew
PMCID:5849499 ; 2018; Journal Anesthesiology; vol. 128; no. 4; pp. 728-744; AWUW5r2FdzjauPDbjhud doi:10.1097/aln.0000000000002103
Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease
X. Liu, P. Cao, J. Yang and D. Zhao
2018; Journal Computational and mathematical methods in medicine; vol. 2018; AWUW5r2FdzjauPDbjhuj
Clinical significance of visually equivocal amyloid PET findings from the Alzheimer’s Disease Neuroimaging Initiative cohort
M. Oh, M. Seo, S. Y. Oh, H. Kim, B. W. Choi, J. S. Oh, J. S. Kim and A. s. D. N. Initiative
2018; Journal NeuroReport; vol. 29; no. 7; pp. 553-558; AWUW5r2FdzjauPDbjhuk
Joint Assessment of Quantitative 18F-Florbetapir and 18F-FDG Regional Uptake Using Baseline Data from the ADNI
F. Ben Bouallegue, D. Mariano-Goulart and P. Payoux
2018; Journal J Alzheimers Dis; vol. 62; no. 1; pp. 399-408; AWUW0BZZdzjauPDbjht0 doi:10.3233/jad-170833
Volumetric comparison of hippocampal subfields extracted from 4-minute accelerated vs. 8-minute high-resolution T2-weighted 3T MRI scans
S. Cong, S. L. Risacher, J. D. West, Y. C. Wu, L. G. Apostolova, E. Tallman, M. Rizkalla, P. Salama, A. J. Saykin and L. Shen
2018; Journal Brain Imaging Behav; AWUW0BZZdzjauPDbjht3 doi:10.1007/s11682-017-9819-3
Microstructural and metabolic changes in the longitudinal progression of white matter hyperintensities
Y. Jiaerken, X. Luo, X. Yu, P. Huang, X. Xu and M. Zhang
2018; Journal J Cereb Blood Flow Metab; pp. 271678x18761438; AWUW0BZZdzjauPDbjht8 doi:10.1177/0271678x18761438
Incremental Validity of Montreal Cognitive Assessment Index Scores in Mild Cognitive Impairment and Alzheimer Disease
F. C. Goldstein, A. Milloy, D. W. Loring and A. s. D. N. Initiative
2018; Journal Dementia and geriatric cognitive disorders; vol. 45; no. 1; pp. 49-55; AWUW5A4cdzjauPDbjhuX
Can measuring hippocampal atrophy with a fully automatic method be substantially less noisy than manual segmentation over both 1 and 3 years?
Cover, K. S., van Schijndel, R. A., Bosco, P., Damangir, S. and Redolfi, A.
PMID: 30149361 ; 2018; Journal Psychiatry Res Neuroimaging; vol. 280; pp. 39-47; AW5HwZDTMOwVf_qbJr_o