Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification-Reference-Cited by-同舟云学术

Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification

Published:2024 Issue: Volume: Page:202-216
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:en
Short-container-title:

Author:

Tinauer Christian^ORCID,Damulina Anna^ORCID,Sackl Maximilian^ORCID,Soellradl Martin^ORCID,Achtibat Reduan^ORCID,Dreyer Maximilian^ORCID,Pahde Frederik^ORCID,Lapuschkin Sebastian^ORCID,Schmidt Reinhold^ORCID,Ropele Stefan^ORCID,Samek Wojciech^ORCID,Langkammer Christian^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-63797-1_11

Reference25 articles.

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3. Bach, S., Binder, A., Montavon, G., Klauschen, F., Müller, K.R., Samek, W.: On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation. PLOS ONE 10(7), e0130140 (2015). https://doi.org/10.1371/journal.pone.0130140. https://dx.plos.org/10.1371/journal.pone.0130140

4. Bouthillier, X., et al.: Accounting for variance in machine learning benchmarks, March 2021. arXiv arXiv:2103.03098 [cs, stat]. https://doi.org/10.48550/arXiv.2103.03098

5. Böhle, M., Eitel, F., Weygandt, M., Ritter, K.: Layer-wise relevance propagation for explaining deep neural network decisions in MRI-based Alzheimer’s disease classification. Front. Aging Neurosci. 11, 194 (2019). https://doi.org/10.3389/fnagi.2019.00194