Interpreting SVM for medical images using Quadtree

In this paper, we propose a quadtree based approach to capture the spatial information of medical images for explaining nonlinear SVM prediction. In medical image classification, interpretability becomes important to understand why the adopted model works. Explaining an SVM prediction is difficult d...

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Detalles Bibliográficos
Autores principales: Shukla, Prashant, Verma, Abhishek, Abhishek, Verma, Shekhar, Kumar, Manish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7417748/
https://www.ncbi.nlm.nih.gov/pubmed/32837249
http://dx.doi.org/10.1007/s11042-020-09431-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7417748/
https://www.ncbi.nlm.nih.gov/pubmed/32837249
http://dx.doi.org/10.1007/s11042-020-09431-2

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