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Publication AI

The ADNI publication AI is a multi-lingual system capable of answering questions in multiple languages. Its responses are primarily based on information from ADNI publications.

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*This AI can be a helpful starting point, but it’s not perfect. The information provided by this Retrieval-Augmented Generation (RAG) system may be incomplete or limited in scope due to embargo restrictions on certain publications. These embargoes prevent access to data, research, or content that has not yet been officially released to the public or approved for distribution. As a result, the system’s knowledge base may lack the most recent updates, studies, or materials related to specific topics. Please double‑check any references, facts, or details before relying on them. The creators and operators of this AI system are not liable for any consequences, decisions, or actions taken based on its output. When in doubt, it’s always best to confirm things with authoritative sources.

Publication Search

ADNI publication pdfs can be searched by year, journal, author, or keyword using the search boxes below.

6413 Total Publications

Year	Title	Author	Journal
2020	Multimodal Phenotyping of Alzheimer's Disease with Longitudinal Magnetic Resonance Imaging and Cognitive Function Data	Kim, Y, Jiang, X, Giancardo, L, Pena, D, Bukhbinder, AS, Amran, AY and Schulz, PE	Journal Sci Rep;
2020	Attention-Guided Hybrid Network for Dementia Diagnosis With Structural MR Images	Lian, C, Liu, M, Pan, Y and Shen, D	Journal IEEE Trans Cybern;
2020	Assessment of Tau Tangles and Amyloid-beta Plaques Among Super Agers Using PET Imaging	Hoenig, MC, Willscheid, N, Bischof, GN, van Eimeren, T, Drzezga, A and Alzheimers Dis, N	Journal Jama Network Open;
2020	Minimum variance-embedded deep kernel regularized least squares method for one-class classification and its applications to biomedical data	Gautam, C, Mishra, PK, Tiwari, A, Richhariya, B, Pandey, HM, Wang, SH, Tanveer, M and Alzheimers Dis Neuroimaging, I	Journal Neural Networks;
2020	Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging	Bae, JB, Lee, S, Jung, W, Park, S, Kim, W, Oh, H, Han, JW, Kim, GE, Kim, JS, Kim, JH and Kim, KW	Journal Sci Rep;
2020	Hybrid simulation modelling for dementia care services planning	Evenden, DC, Brailsford, SC, Kipps, CM, Roderick, PJ, Walsh, B and Alzheimers Dis Neuroimaging, I	Journal Journal of the Operational Research Society;
2020	Ensemble of deep convolutional neural networks based multi-modality images for Alzheimer's disease diagnosis	Fang, XS, Liu, ZB and Xu, MC	Journal Iet Image Processing;
2020	Functional ensemble survival tree: Dynamic prediction of Alzheimer's disease progression accommodating multiple time-varying covariates	Jiang, S, Xie, YJ and Colditz, GA	Journal Journal of the Royal Statistical Society Series C-Applied Statistics;
2020	Optimized One vs One Approach in Multiclass Classification for Early Alzheimer's Disease and Mild Cognitive Impairment Diagnosis	Jimenez-Mesa, C, Illan, IA, Martin-Martin, A, Castillo-Barnes, D, Martinez-Murcia, FJ, Ramirez, J and Gorriz, JM	Journal Ieee Access;
2020	Robust hybrid deep learning models for Alzheimer’s progression detection	Abuhmed, T, El-Sappagh, S and Alonso, JM	Journal Knowledge-Based Systems;

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