Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning

To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progres...

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Detalles Bibliográficos
Autores principales: Scotton, William J, Shand, Cameron, Todd, Emily, Bocchetta, Martina, Cash, David M, VandeVrede, Lawren, Heuer, Hilary, Young, Alexandra L, Oxtoby, Neil, Alexander, Daniel C, Rowe, James B, Morris, Huw R, Boxer, Adam L, Rohrer, Jonathan D, Wijeratne, Peter A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10016410/
https://www.ncbi.nlm.nih.gov/pubmed/36938523
http://dx.doi.org/10.1093/braincomms/fcad048

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10016410/
https://www.ncbi.nlm.nih.gov/pubmed/36938523
http://dx.doi.org/10.1093/braincomms/fcad048

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