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

U-M 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.

Written by: Michigan Engineering

April 4, 2017

portraitLauren Steimle
PhD Student of Industrial and Operations Engineering
portraitBrian Denton
Professor of Industrial and Operations Engineering

PEOPLE:

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.

portrait of Brian Denton and Lauren Steimle
portrait of Brian Denton and Lauren Steimle

Denton and 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, also included Rodney Hayward, and Jeremy Sussman, and Stanford biostatistician Joseph Rigdon. 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.

Explore: Awards Data Analytics Doctoral Students Faculty Health and Human Safety Brian Denton

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