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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
2013	Mapping creatinine- and cystatin C-related white matter brain deficits in the elderly.	Rajagopalan, P., Refsum, H., Hua, X., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M.	Journal Neurobiology of Aging;
2013	Evaluating Alzheimer’s disease progression using rate of regional hippocampal atrophy.	Frankó, E., & Joly, O.	Journal PloS One;
2013	Multiple instance learning for classification of dementia in brain MRI.	Tong, T., Wolz, R., Gao, Q., Hajnal, J. V, & Rueckert, D.	Journal Medical Image Computing and Computer-Assisted Intervention;
2013	Large Deformation Image Classification Using Generalized Locality-Constrained Linear Coding.	Zhang, P., Wee, C., Niethammer, M., & Shen, D.	Journal Medical Image Computing and Computer-Assisted Intervention;
2013	Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling.	Tong, T., Wolz, R., Coupé, P., Hajnal, J. V, & Rueckert, D.	Journal Neuroimage;
2013	Modeling the heterogeneity in risk of progression to Alzheimer’s disease across cognitive profiles in mild cognitive impairment.	Tatsuoka, C., Tseng, H., Jaeger, J., Varadi, F., Smith, M. A., Yamada, T., … Lerner, A. J.	Journal Alzheimer's Research and Therapy;
2013	Locally linear embedding (LLE) for MRI based Alzheimer’s disease classification.	Liu, X., Tosun, D., Weiner, M. W., & Schuff, N.	Journal Neuroimage;
2013	Predicting brain activity using a Bayesian spatial model.	Derado, G., Bowman, F. D., & Zhang, L.	Journal Statistical Methods in Medical Research;
2013	Brain size and the compensation of Alzheimer's disease symptoms: A longitudinal cohort study	Guo, L.-H., Alexopoulos, P., Wagenpfeil, S., Kurz, A., & Perneczky, R.	Journal Alzheimer's and Dementia;
2013	A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies	Khondoker, M., Dobson, R., Skirrow, C., Simmons, A., & Stahl, D.	Journal Statistical Methods in Medical Research;

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