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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...
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| Pubblicato in: | Nat Commun |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6520374/ https://ncbi.nlm.nih.gov/pubmed/31092819 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-019-10212-1 |
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