Cargando…
Prediction of early breast cancer patient survival using ensembles of hypoxia signatures
BACKGROUND: Biomarkers are a key component of precision medicine. However, full clinical integration of biomarkers has been met with challenges, partly attributed to analytical difficulties. It has been shown that biomarker reproducibility is susceptible to data preprocessing approaches. Here, we sy...
Autores principales: | Gong, Inna Y., Fox, Natalie S., Huang, Vincent, Boutros, Paul C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138385/ https://www.ncbi.nlm.nih.gov/pubmed/30216362 http://dx.doi.org/10.1371/journal.pone.0204123 |
Ejemplares similares
-
Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences
por: Fox, Natalie S, et al.
Publicado: (2014) -
A transcriptome-based signature of pathological angiogenesis predicts breast cancer patient survival
por: Guarischi-Sousa, Rodrigo, et al.
Publicado: (2019) -
A combined hypoxia and immune gene signature for predicting survival and risk stratification in triple-negative breast cancer
por: Yang, Xia, et al.
Publicado: (2021) -
An Ensembled Framework for Human Breast Cancer Survivability Prediction Using Deep Learning
por: Mustafa, Ehzaz, et al.
Publicado: (2023) -
SVM and SVM Ensembles in Breast Cancer Prediction
por: Huang, Min-Wei, et al.
Publicado: (2017)