Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression

Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer’s disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clu...

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Detalles Bibliográficos
Autores principales: Poulakis, Konstantinos, Ferreira, Daniel, Pereira, Joana B., Smedby, Örjan, Vemuri, Prashanthi, Westman, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7377879/
https://www.ncbi.nlm.nih.gov/pubmed/32644944
http://dx.doi.org/10.18632/aging.103623

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7377879/
https://www.ncbi.nlm.nih.gov/pubmed/32644944
http://dx.doi.org/10.18632/aging.103623

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