PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma

MOTIVATION: Convolutional neural networks (CNNs) have achieved great success in the areas of image processing and computer vision, handling grid-structured inputs and efficiently capturing local dependencies through multiple levels of abstraction. However, a lack of interpretability remains a key ba...

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Detalles Bibliográficos
Autores principales: Oh, Jung Hun, Choi, Wookjin, Ko, Euiseong, Kang, Mingon, Tannenbaum, Allen, Deasy, Joseph O
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
General Computational Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336441/
https://www.ncbi.nlm.nih.gov/pubmed/34252964
http://dx.doi.org/10.1093/bioinformatics/btab285

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336441/
https://www.ncbi.nlm.nih.gov/pubmed/34252964
http://dx.doi.org/10.1093/bioinformatics/btab285

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