Interpretable classification of Alzheimer’s disease pathologies with a convolutional neural network pipeline

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific n...

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Detalles Bibliográficos
Autores principales: Tang, Ziqi, Chuang, Kangway V., DeCarli, Charles, Jin, Lee-Way, Beckett, Laurel, Keiser, Michael J., Dugger, Brittany N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6520374/
https://www.ncbi.nlm.nih.gov/pubmed/31092819
http://dx.doi.org/10.1038/s41467-019-10212-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6520374/
https://www.ncbi.nlm.nih.gov/pubmed/31092819
http://dx.doi.org/10.1038/s41467-019-10212-1

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