Improved performance on high-dimensional survival data by application of Survival-SVM.
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NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.Learning rule sets from survival data.Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetesA network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.Large-scale parametric survival analysisSurvival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression.High-dimensional, massive sample-size Cox proportional hazards regression for survival analysisNetwork-based sub-network signatures unveil the potential for acute myeloid leukemia therapy.Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.Prognostic relevance and performance characteristics of serum IGFBP-2 and PAPP-A in women with breast cancer: a long-term Danish cohort study.
P2860
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P2860
Improved performance on high-dimensional survival data by application of Survival-SVM.
description
2010 nî lūn-bûn
@nan
2010 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Improved performance on high-dimensional survival data by application of Survival-SVM.
@ast
Improved performance on high-dimensional survival data by application of Survival-SVM.
@en
type
label
Improved performance on high-dimensional survival data by application of Survival-SVM.
@ast
Improved performance on high-dimensional survival data by application of Survival-SVM.
@en
prefLabel
Improved performance on high-dimensional survival data by application of Survival-SVM.
@ast
Improved performance on high-dimensional survival data by application of Survival-SVM.
@en
P2093
P356
P1433
P1476
Improved performance on high-dimensional survival data by application of Survival-SVM.
@en
P2093
J A K Suykens
K Pelckmans
S Van Huffel
V Van Belle
P356
10.1093/BIOINFORMATICS/BTQ617
P407
P577
2010-11-08T00:00:00Z