Learning from small medical data—robust semi-supervised cancer prognosis classifier with Bayesian variational autoencoder

MOTIVATION: Cancer is one of the world’s leading mortality causes, and its prognosis is hard to predict due to complicated biological interactions among heterogeneous data types. Numerous challenges, such as censorship, high dimensionality and small sample size, prevent researchers from using deep l...

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Detalles Bibliográficos
Autores principales: Hsu, Te-Cheng, Lin, Che
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/PMC9832968/
https://www.ncbi.nlm.nih.gov/pubmed/36698767
http://dx.doi.org/10.1093/bioadv/vbac100

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832968/
https://www.ncbi.nlm.nih.gov/pubmed/36698767
http://dx.doi.org/10.1093/bioadv/vbac100

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