BIOMARKERS FOR SCREENING, PREDICTING, AND MONITORING BENIGN PROSTATE HYPERPLASIA
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app pub date -
Jul 26, 2007
filing date -
May 1, 1998
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Abandoned
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Abstract
Gene expression data are analyzed using learning machines such as support vector machines (SVM) and ridge regression classifiers to rank genes according to their ability to distinguish between BPH (benign prostatic hyperplasia) and all other conditions. Results are provided showing the correlation of results obtained using data from two independent studies that took place at different times using different microarrays. Genes are ranked according to area-under-the-curve, false discovery rate and fold change.
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