4453 Total Publications
A Conformation Variant of p53 Combined with Machine Learning Identifies Alzheimer Disease in Preclinical and Prodromal Stages
Abate, G, Vezzoli, M, Polito, L, Guaita, A, Albani, D, Marizzoni, M, Garrafa, E, Marengoni, A, Forloni, G, Frisoni, GB, Cummings, JL, Memo, M and Uberti, D
2020; Journal J Pers Med; vol. 11; no. 1;
Deep residual learning for neuroimaging: An application to predict progression to Alzheimer's disease
Abrol, A, Bhattarai, M, Fedorov, A, Du, YH, Plis, S, Calhoun, V and Alzheimers Dis Neuroimaging, I
2020; Journal Journal of Neuroscience Methods; vol. 339;
Deep and joint learning of longitudinal data for Alzheimer's disease prediction
Lei, B, Yang, M, Yang, P, Zhou, F, Hou, W, Zou, W, Li, X, Wang, T, Xiao, X and Wang, S
2020; Journal Pattern Recognition; vol. 102; pp. 107247;
MuscNet, a Weighted Voting Model of Multi-Source Connectivity Networks to Predict Mild Cognitive Impairment Using Resting-State Functional MRI
Li, JL, Yao, ZM, Duan, MY, Liu, S, Li, F, Zhu, HY, Xia, ZQ, Huang, L and Zhou, FF
2020; Journal Ieee Access; vol. 8; pp. 174023-174031;
Alzheimer's disease biomarkers as predictors of trajectories of depression and apathy in cognitively normal individuals, mild cognitive impairment, and Alzheimer's disease dementia
Banning, LCP, Ramakers, I, Rosenberg, PB, Lyketsos, CG and Leoutsakos, JS
2020; Journal Int J Geriatr Psychiatry;
Stage-specific links between plasma neurofilament light and imaging biomarkers of Alzheimer’s disease
Benedet, AL, Leuzy, A, Pascoal, TA, Ashton, NJ, Mathotaarachchi, S, Savard, M, Therriault, J, Kang, MS, Chamoun, M and Schöll, M
2020; Journal Brain; vol. 143; pp. 3793-3804;