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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...
Autores principales: | Tang, Ziqi, Chuang, Kangway V., DeCarli, Charles, Jin, Lee-Way, Beckett, Laurel, Keiser, Michael J., Dugger, Brittany N. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
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 |
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