Robust Biomarker Identification For Cancer Diagnosis With Ensemble Feature Selection Methods..pdf

ensemble_bioinformatics.pdf
Preview of Robust biomarker identification for cancer diagnosis with ensemble feature selection methods.
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📊 Size: 266 KB
📄 Pages: 7 pages
⬇️ Downloads: 99

Summary

Biomarker discovery is crucial in cancer diagnosis, and feature selection is key to identifying relevant biomarkers. However, the stability of feature selection methods has received little attention. This study proposes a framework for analyzing the robustness of biomarker selection algorithms and introduces ensemble feature selection methods to increase robustness. Using support vector machines (SVMs) and ensemble feature selection, the study demonstrates improved robustness and classification performance on four microarray data sets, with increases of up to 30% in robustness and 15% in classification performance.

Description

Biomarker discovery is crucial in cancer diagnosis, and feature selection is key to identifying relevant biomarkers.

Technical Information

  • File Format: PDF
  • File Size: 266 KB
  • Pages: 7
  • Language: EN
  • Total Downloads: 99
  • Last Updated: 7 days ago

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