Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data

SIMPLE SUMMARY: Here, we compared the performance of four different autoencoders: (a) vanilla, (b) sparse, (c) denoising, and (d) variational for subtype detection on four cancer types: Glioblastoma multiforme, Colon Adenocarcinoma, Kidney renal clear cell carcinoma, and Breast invasive carcinoma. M...

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Detalles Bibliográficos
Autores principales: Franco, Edian F., Rana, Pratip, Cruz, Aline, Calderón, Víctor V., Azevedo, Vasco, Ramos, Rommel T. J., Ghosh, Preetam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8122584/
https://www.ncbi.nlm.nih.gov/pubmed/33921978
http://dx.doi.org/10.3390/cancers13092013

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8122584/
https://www.ncbi.nlm.nih.gov/pubmed/33921978
http://dx.doi.org/10.3390/cancers13092013

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