Colorectal Cancer Survival Prediction Using Deep Distribution Based Multiple-Instance Learning

Most deep-learning algorithms that use Hematoxylin- and Eosin-stained whole slide images (WSIs) to predict cancer survival incorporate image patches either with the highest scores or a combination of both the highest and lowest scores. In this study, we hypothesize that incorporating wholistic patch...

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Detalles Bibliográficos
Autores principales: Li, Xingyu, Jonnagaddala, Jitendra, Cen, Min, Zhang, Hong, Xu, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689861/
https://www.ncbi.nlm.nih.gov/pubmed/36421523
http://dx.doi.org/10.3390/e24111669

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689861/
https://www.ncbi.nlm.nih.gov/pubmed/36421523
http://dx.doi.org/10.3390/e24111669

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