HFBSurv: hierarchical multimodal fusion with factorized bilinear models for cancer survival prediction

MOTIVATION: Cancer survival prediction can greatly assist clinicians in planning patient treatments and improving their life quality. Recent evidence suggests the fusion of multimodal data, such as genomic data and pathological images, is crucial for understanding cancer heterogeneity and enhancing...

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Detalles Bibliográficos
Autores principales: Li, Ruiqing, Wu, Xingqi, Li, Ao, Wang, Minghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048674/
https://www.ncbi.nlm.nih.gov/pubmed/35188177
http://dx.doi.org/10.1093/bioinformatics/btac113

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048674/
https://www.ncbi.nlm.nih.gov/pubmed/35188177
http://dx.doi.org/10.1093/bioinformatics/btac113

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