Interpretable brain disease classification and relevance-guided deep learning

Deep neural networks are increasingly used for neurological disease classification by MRI, but the networks’ decisions are not easily interpretable by humans. Heat mapping by deep Taylor decomposition revealed that (potentially misleading) image features even outside of the brain tissue are crucial...

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Detalles Bibliográficos
Autores principales: Tinauer, Christian, Heber, Stefan, Pirpamer, Lukas, Damulina, Anna, Schmidt, Reinhold, Stollberger, Rudolf, Ropele, Stefan, Langkammer, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9691637/
https://www.ncbi.nlm.nih.gov/pubmed/36424437
http://dx.doi.org/10.1038/s41598-022-24541-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9691637/
https://www.ncbi.nlm.nih.gov/pubmed/36424437
http://dx.doi.org/10.1038/s41598-022-24541-7

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