Sparse kernel methods for high-dimensional survival data.
about
Big data in medical science--a biostatistical viewIntegration of pathway structure information into a reweighted partial Cox regression approach for survival analysis on high-dimensional gene expression data.Online Censoring for Large-Scale Regressions with Application to Streaming Big DataPathway analysis using random forests with bivariate node-split for survival outcomesAn overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.Gene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithmPredicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT.A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.Gene selection using iterative feature elimination random forests for survival outcomes.Large-scale parametric survival analysisA gradient boosting algorithm for survival analysis via direct optimization of concordance indexHigh-dimensional, massive sample-size Cox proportional hazards regression for survival analysisModeling time-to-event (survival) data using classification tree analysis.Topologically inferring pathway activity for precise survival outcome prediction: breast cancer as a case.Joint Covariate Detection on Expression Profiles for Selecting Prognostic miRNAs in Glioblastoma.Feature Subset Selection for Cancer Classification Using Weight Local Modularity.Network-based sub-network signatures unveil the potential for acute myeloid leukemia therapy.Survival analysis by penalized regression and matrix factorization.A robust hybrid approach based on estimation of distribution algorithm and support vector machine for hunting candidate disease genes.JCDSA: a joint covariate detection tool for survival analysis on tumor expression profiles.Active Learning based Survival Regression for Censored Data
P2860
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P2860
Sparse kernel methods for high-dimensional survival data.
description
2008 nî lūn-bûn
@nan
2008 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年学术文章
@wuu
2008年学术文章
@zh-cn
2008年学术文章
@zh-hans
2008年学术文章
@zh-my
2008年学术文章
@zh-sg
2008年學術文章
@yue
name
Sparse kernel methods for high-dimensional survival data.
@ast
Sparse kernel methods for high-dimensional survival data.
@en
type
label
Sparse kernel methods for high-dimensional survival data.
@ast
Sparse kernel methods for high-dimensional survival data.
@en
prefLabel
Sparse kernel methods for high-dimensional survival data.
@ast
Sparse kernel methods for high-dimensional survival data.
@en
P2860
P356
P1433
P1476
Sparse kernel methods for high-dimensional survival data.
@en
P2093
Ludger Evers
P2860
P304
P356
10.1093/BIOINFORMATICS/BTN253
P407
P577
2008-05-30T00:00:00Z