Modeling autosomal dominant Alzheimer’s disease with machine learning

INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer’s disease. METHODS: Longitudinal structural MRI, amyloid PET, and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Al...

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izdano v:Alzheimers Dement
Main Authors: Luckett, Patrick H., McCullough, Austin, Gordon, Brian A., Strain, Jeremy, Flores, Shaney, Dincer, Aylin, McCarthy, John, Kuffner, Todd, Stern, Ari, Meeker, Karin L., Berman, Sarah B., Chhatwal, Jasmeer P., Cruchaga, Carlos, Fagan, Anne M., Farlow, Martin R., Fox, Nick C., Jucker, Mathias, Levin, Johannes, Masters, Colin L., Mori, Hiroshi, Noble, James M., Salloway, Stephen, Schofield, Peter R., Brickman, Adam M., Brooks, William S., Cash, David M., Fulham, Michael J., Ghetti, Bernardino, Jack, Clifford R., Vöglein, Jonathan, Klunk, William, Koeppe, Robert, Oh, Hwamee, Su, Yi, Weiner, Michael, Wang, Qing, Swisher, Laura, Marcus, Dan, Koudelis, Deborah, Joseph-Mathurin, Nelly, Cash, Lisa, Hornbeck, Russ, Xiong, Chengjie, Perrin, Richard J., Karch, Celeste M., Hassenstab, Jason, McDade, Eric, Morris, John C., Benzinger, Tammie L.S., Bateman, Randall J., Ances, Beau M.
Format: Artigo
Jezik:Inglês
Izdano: 2021
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Article
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC8195816/
https://ncbi.nlm.nih.gov/pubmed/33480178
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/alz.12259
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