Cargando…
BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data
BACKGROUND: The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest mode...
Autores principales: | Guo, Yang, Liu, Shuhui, Li, Zhanhuai, Shang, Xuequn |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907304/ https://www.ncbi.nlm.nih.gov/pubmed/29671390 http://dx.doi.org/10.1186/s12859-018-2095-4 |
Ejemplares similares
-
Improvement of cancer subtype prediction by incorporating transcriptome expression data and heterogeneous biological networks
por: Guo, Yang, et al.
Publicado: (2018) -
A Similarity Regression Fusion Model for Integrating Multi-Omics Data to Identify Cancer Subtypes
por: Guo, Yang, et al.
Publicado: (2018) -
A Cascade Flexible Neural Forest Model for Cancer Subtypes Classification on Gene Expression Data
por: Zhong, Lianxin, et al.
Publicado: (2021) -
A laminar augmented cascading flexible neural forest model for classification of cancer subtypes based on gene expression data
por: Zhong, Lianxin, et al.
Publicado: (2021) -
A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data
por: Xu, Jing, et al.
Publicado: (2019)