On the use of double cross-validation for the combination of proteomic mass spectral data for enhanced diagnosis and prediction

DOI10.1016/j.spl.2011.02.037zbMath1217.62184OpenAlexW2067453181MaRDI QIDQ544613

W. E. Mesker, Y. E. M. Van Der Burgt, Bart Mertens, B. Velstra, R. A. E. M. Tollenaar, André M. Deelder

Publication date: 15 June 2011

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2011.02.037

zbMATH Keywords

classificationmodel combinationclinical mass spectrometry proteomicspredictive data fusion

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biomedical imaging and signal processing (92C55) Medical applications (general) (92C50)

Related Items (1)

Sequential double cross-validation for assessment of added predictive ability in high-dimensional omic applications

Uses Software

• Matlab

Cites Work

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• Stacked regressions
• Classifier technology and the illusion of progress
• Organizing a Competition on Clinical Mass Spectrometry Based Proteomic Diagnosis
• Two further applications of a model for binary regression
• Exact Principal Component Influence Measures Applied to the Analysis of Spectroscopic Data on Rice
• Downdating: Interdisciplinary Research Between Statistics and Computing
• Random forests

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