Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification

MOTIVATION: Multiple instance learning (MIL) is a powerful technique to classify whole slide images (WSIs) for diagnostic pathology. The key challenge of MIL on WSI classification is to discover the critical instances that trigger the bag label. However, tumor heterogeneity significantly hinders the...

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Detalles Bibliográficos
Autores principales: Wang, Zhikang, Bi, Yue, Pan, Tong, Wang, Xiaoyu, Bain, Chris, Bassed, Richard, Imoto, Seiya, Yao, Jianhua, Daly, Roger J, Song, Jiangning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023223/
https://www.ncbi.nlm.nih.gov/pubmed/36864612
http://dx.doi.org/10.1093/bioinformatics/btad114

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023223/
https://www.ncbi.nlm.nih.gov/pubmed/36864612
http://dx.doi.org/10.1093/bioinformatics/btad114

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