Barnett C, Merdan S. Data analytics for optimal detection of metastatic prostate cancer. Presented at the 2016 INFORMS Annual Meeting; November 13, 2016. Nashville, TN.

We used data-analytics approaches to develop, calibrate, and validate predictive models to help urologists make prostate cancer staging decisions. These models were used to design guidelines that weigh the benefits and harms of radiological imaging. The Michigan Urological Surgery Improvement Collaborative implemented these guidelines which miss less than 1% of metastatic cancers while reducing unnecessary imaging by more than 40%.

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