Cargando…
Molecular Prognostic Prediction for Locally Advanced Nasopharyngeal Carcinoma by Support Vector Machine Integrated Approach
BACKGROUND: Accurate prognostication of locally advanced nasopharyngeal carcinoma (NPC) will benefit patients for tailored therapy. Here, we addressed this issue by developing a mathematical algorithm based on support vector machine (SVM) through integrating the expression levels of multi-biomarkers...
Autores principales: | Wan, Xiang-Bo, Zhao, Yan, Fan, Xin-Juan, Cai, Hong-Min, Zhang, Yan, Chen, Ming-Yuan, Xu, Jie, Wu, Xiang-Yuan, Li, Hong-Bo, Zeng, Yi-Xin, Hong, Ming-Huang, Liu, Quentin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3302890/ https://www.ncbi.nlm.nih.gov/pubmed/22427815 http://dx.doi.org/10.1371/journal.pone.0031989 |
Ejemplares similares
-
A Novel Support Vector Machine with Globality-Locality Preserving
por: Ma, Cheng-Long, et al.
Publicado: (2014) -
The Prognostic Value of Treatment-Related Lymphopenia in Nasopharyngeal Carcinoma Patients
por: Liu, Li-Ting, et al.
Publicado: (2018) -
Development of a ten-signature classifier using a support vector machine integrated approach to subdivide the M1 stage into M1a and M1b stages of nasopharyngeal carcinoma with synchronous metastases to better predict patients' survival
por: Jiang, Rou, et al.
Publicado: (2015) -
Effective Pneumothorax Detection for Chest X-Ray Images Using Local Binary Pattern and Support Vector Machine
por: Chan, Yuan-Hao, et al.
Publicado: (2018) -
Integrated application of uniform design and least-squares support vector machines to transfection optimization
por: Pan, Jin-Shui, et al.
Publicado: (2009)