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The goal of this study is to apply cutting-edge imaging approaches, incorporating machine-learning for pattern recognition and multispectral analysis, to the development and validation of intermediate endpoint biomarkers in benign tissue that characterize the response to 5α-reductase inhibitor chemoprevention as well as the risk of prostate cancer among men with negative biopsies.
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139 participants in 6 patient groups
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Data sourced from clinicaltrials.gov
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