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Publication AI | Publication Search

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.

6006 Total Publications

Year	Title	Author	Journal
2020	An Efficient Combination among sMRI, CSF, Cognitive Score, and APOE ε4 Biomarkers for Classification of AD and MCI Using Extreme Learning Machine	Khatri, U and Kwon, G-R	Journal Computational Intelligence and Neuroscience;
2020	Differential Diagnosis of Frontotemporal Dementia, Alzheimer's Disease, and Normal Aging Using a Multi-Scale Multi-Type Feature Generative Adversarial Deep Neural Network on Structural Magnetic Resonance Images	Ma, D, Lu, D, Popuri, K, Wang, L and Beg, MF	Journal Front Neurosci;
2020	Studying the Manifold Structure of Alzheimers Disease: A Deep Learning Approach Using Convolutional Autoencoders	Martinez-Murcia, FJ, Ortiz, A, Gorriz, JM, Ramirez, J and Castillo-Barnes, D	Journal Ieee Journal of Biomedical and Health Informatics;
2020	CSF VEGF Was Positively Associated with Neurogranin Independent of beta-Amyloid Pathology	Huang, YP, Wang, J, Zhu, BH and Fu, P	Journal Neuropsychiatric Disease and Treatment;
2020	Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease	Huynh, K, Lim, WLF, Giles, C, Jayawardana, KS, Salim, A, Mellett, NA, Smith, AAT, Olshansky, G, Drew, BG, Chatterjee, P, Martins, I, Laws, SM, Bush, AI, Rowe, CC, Villemagne, VL, Ames, D, Masters, CL, Arnold, M, Nho, K, Saykin, AJ, Baillie, R, Han, X, Kaddurah-Daouk, R, Martins, RN and Meikle, PJ	Journal Nat Commun;
2020	Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) Found by Hierarchical Clustering	Kärkkäinen, M, Prakash, M, Zare, M, Tohka, J and For The Alzheimer's Disease Neuroimaging, I	Journal Int J Alzheimers Dis;
2020	Hallucinations and Delusions Signal Alzheimer's Associated Cognitive Dysfunction More Strongly Compared to Other Neuropsychiatric Symptoms	Fuller, JT, Choudhury, TK, Lowe, DA and Balsis, S	Journal J Gerontol B Psychol Sci Soc Sci;
2020	AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction	Gao, F, Yoon, H, Xu, YZ, Goradia, D, Luo, J, Wu, T, Su, Y and Alzheimers Dis Neuroimaging, I	Journal Neuroimage-Clinical;
2020	Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease	Giorgio, J, Landau, SM, Jagust, WJ, Tino, P and Kourtzi, Z	Journal Neuroimage Clin;
2020	Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease	Meng, XL, Li, J, Zhang, QS, Chen, F, Bian, CY, Yao, XH, Yan, JW, Xu, Z, Risacher, SL, Saykin, AJ, Liang, H, Shen, L and Alzheimers Dis Neuroimaging, I	Journal Bmc Genomics;

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2026 Alzheimer’s Disease Neuroimaging Initiative

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Due to serious data quality concerns, all data with PTIDs containing the format 381_S_10### have been removed from the ADNI data repository. ADNI leadership strongly advises that data with these PTIDs not be used in any data analysis, submission of abstracts, or publications. Furthermore, ADNI leadership requests that any abstracts or papers which have been submitted using this data be appropriately revised due to concerns with data quality. More information click here.

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