Predicting sporadic Alzheimer’s disease progression via inherited Alzheimer’s disease-informed machine-learning

INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer’s disease (AD) is a critical yet unmet clinical challenge. METHODS: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magn...

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Detalles Bibliográficos
Autores principales: Franzmeier, Nicolai, Koutsouleris, Nikolaos, Benzinger, Tammie, Goate, Alison, Karch, Celeste M., Fagan, Anne M., McDade, Eric, Duering, Marco, Dichgans, Martin, Levin, Johannes, Gordon, Brian A., Lim, Yen Ying, Masters, Colin L., Rossor, Martin, Fox, Nick C., O’Connor, Antoinette, Chhatwal, Jasmeer, Salloway, Stephen, Danek, Adrian, Hassenstab, Jason, Schofield, Peter R., Morris, John C., Bateman, Randall J., Ewers, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7222030/
https://www.ncbi.nlm.nih.gov/pubmed/32043733
http://dx.doi.org/10.1002/alz.12032

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7222030/
https://www.ncbi.nlm.nih.gov/pubmed/32043733
http://dx.doi.org/10.1002/alz.12032

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