Interpretable classification of Alzheimer’s disease pathologies with a convolutional neural network pipeline
Convolutional neural networks have been applied to various areas of medical imaging and histology. Here the authors develop an automated approach using interpretable neural networks to determine Alzheimer’s disease plaque and cerebral amyloid angiopathy burden in post-mortem human brain tissue.
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| Auteurs principaux: | , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2019
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/ba915e392b8548368af02fe9f5bed428 |
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