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Multivariate Biomarker Discovery from Part IV - Biomarker Discovery via Multistage Signal Enhancement and Identification of Essential Patterns
Published online by Cambridge University Press: 30 May 2024
Chapter 15 starts with the identification of essential patterns by analyzing distributions of groups of variables (with similar patterns) among a large number of optimal-size biomarkers generated by parallel feature selection experiments. A similar approach leads to the identification of the essential variables of those essential patterns. As a result, the final multivariate biomarker identified via this method is most likely to represent a real population pattern associated with biological processes underlying changes in the investigated response variable. Furthermore, having the variables of the final biomarker associated with their respective essential patterns facilitates biological interpretation of the biomarker.
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