Biomarkers for screening, predicting, and monitoring prostate disease
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United States of America Patent
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Nov 14, 2005
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May 1, 1998
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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 separate prostate cancer from BPH (benign prostatic hyperplasia) and to distinguish cancer volume. Other tests identify biomarker candidates for distinguishing between tumor (Grade 3 and Grade 4 (G3/4)) and normal tissue.
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