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Brian Denton and Lauren Steimle awarded third place in SPRINT Data Challenge

IOE Professor Brian Denton and doctoral student Lauren Steimle are part of the team that claimed third prize in the New England Journal of Medicine's SPRINT Data Challenge.| Short Read
EnlargePortrait of Lauren Steimle and Brian Denton. Photo: Joseph Xu, Michigan Engineering.
IMAGE:  Lauren Steimle and Brian Denton. Photo: Joseph Xu, Michigan Engineering.

U-M Industrial and Operations Engineering (IOE) Professor Brian Denton and PhD student Lauren Steimle are part of the team that claimed third prize in the New England Journal of Medicine’s SPRINT Data Challenge, which allowed teams from around the world to compete to create new knowledge and tools from the raw data of a major clinical trial for hypertension.  The global research community actively engaged with the SPRINT Challenge resulting in 200 qualifying teams from around the world, who submitted 143 Challenge Round entries that identified a novel scientific or clinical finding.

IOE Professor Brian Denton and PhD student Lauren Steimle are part of the team that claimed third prize in the New England Journal of Medicine’s SPRINT Data Challenge, which allowed teams from around the world to compete to create new knowledge and tools from the raw data of a major clinical trial for hypertension.  The global research community actively engaged with the SPRINT Challenge resulting in 200 qualifying teams from around the world, who submitted 143 Challenge Round entries that identified a novel scientific or clinical finding.

The third place team, led by Stanford University researcher Sanjay Basu, M.D., Ph.D., included Brian Denton, Ph.D., doctoral student Lauren Steimle, Rodney Hayward, M.D., and Jeremy Sussman, M.D., M.Sc.,  and Stanford biostatistician Joseph Rigdon, Ph.D.  The team developed a predictive model that could help clinicians decide if intensive blood pressure treatment is right for their patients. Intensive blood pressure treatment can reduce the chance of having a heart attack, stroke, or other major cardiovascular illness, but may increase the chance of experiencing a serious adverse event, such as kidney failure. The team showed their model could identify those patients most likely to experience benefits and least likely to experience harms of intensive treatment.

Along with the first and second place awardees, they will have the opportunity to present their findings at the Aligning Incentives for Sharing Clinical Trial Data summit and web event on April 3-4, 2017.

Portrait of Lauren Steimle and Brian Denton. Photo: Joseph Xu, Michigan Engineering.
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The electrons absorb laser light and set up “momentum combs” (the hills) spanning the energy valleys within the material (the red line). When the electrons have an energy allowed by the quantum mechanical structure of the material—and also touch the edge of the valley—they emit light. This is why some teeth of the combs are bright and some are dark. By measuring the emitted light and precisely locating its source, the research mapped out the energy valleys in a 2D crystal of tungsten diselenide. Credit: Markus Borsch, Quantum Science Theory Lab, University of Michigan.

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