A simulation-approximation approach to sample size planning for high-dimensional classification studies.
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Simulation of complex data structures for planning of studies with focus on biomarker comparison.Determination of sample size for a multi-class classifier based on single-nucleotide polymorphisms: a volume under the surface approachSample size planning for survival prediction with focus on high-dimensional data.Determination of minimum training sample size for microarray-based cancer outcome prediction-an empirical assessment.Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.Statistical assessment of treatment response in a cancer patient based on pre-therapy and post-therapy FDG-PET scans.Study design in high-dimensional classification analysis.Identification and Clinical Translation of Biomarker Signatures: Statistical Considerations.
P2860
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P2860
A simulation-approximation approach to sample size planning for high-dimensional classification studies.
description
2009 nî lūn-bûn
@nan
2009 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
A simulation-approximation app ...... sional classification studies.
@ast
A simulation-approximation app ...... sional classification studies.
@en
type
label
A simulation-approximation app ...... sional classification studies.
@ast
A simulation-approximation app ...... sional classification studies.
@en
prefLabel
A simulation-approximation app ...... sional classification studies.
@ast
A simulation-approximation app ...... sional classification studies.
@en
P2093
P2860
P356
P1433
P1476
A simulation-approximation app ...... sional classification studies.
@en
P2093
Hans-Marcus Bitter
Jonathan Heller
Michael P S Brown
Perry de Valpine
P2860
P304
P356
10.1093/BIOSTATISTICS/KXP001
P577
2009-02-21T00:00:00Z