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Method and system for robust classification strategy for cancer detection from mass spectrometry data

  • US 20080025591A1
  • Filed: 07/27/2006
  • Published: 01/31/2008
  • Est. Priority Date: 07/27/2006
  • Status: Active Grant
First Claim
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1. A robust classification method for cancer detection from mass spectrometry data, comprising:

  • preprocessing mass spectrometry data;

    conducting robust feature selection from the mass spectrometry data;

    generating predictions for test data sets using multiple data classifiers, said multiple data classifiers comprising artificial neural networks, support vector machines, weighted voting on data patterns, classification and regression trees, k-nearest neighbor classification, and logistic regression; and

    constructing and validating a meta-classifier by combining and averaging individual predictions of said multiple data classifiers to generate a robust prediction of a phenotype,wherein said test data sets are used exclusively for validation of the meta-classifier.

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