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17 - Biomarker Discovery Study 2

Multivariate Biomarkers for Liver Cancer

from Part V - Multivariate Biomarker Discovery Studies

Published online by Cambridge University Press:  30 May 2024

Darius M. Dziuda
Darius M. Dziuda
Affiliation:
Central Connecticut State University
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Summary

Chapter 17 describes the second real-life study, whose goal is the identification of multivariate biomarkers for liver cancer. This study implements parallel recursive feature elimination experiments coupled with random forests and support vector machines. Included are also considerations for rebalancing class proportions. Three multivariate biomarkers for liver cancer have been identified. The study has been performed in an R environment, and R scripts for all of its steps are provided.

Keywords

Liver cancerRebalancing class proportionsRecursive feature eliminationParallel experimentsRandom forestsSupport vector machinesRR scripts
Type
Chapter
Information
Multivariate Biomarker Discovery
Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data
 , pp. 241 - 266
Publisher: Cambridge University Press
Print publication year: 2024

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