SAS Analytics tie winter storms to spikes in hospitalizations
SAS Analytics tie winter storms to spikes in hospitalizations
By eGov Innovation Editors | Dec 25, 2011
Using SAS Analytics, a University of Central Florida (UCF) research team won the 5th annual Data Mining Shootout by showing that winter storms had the greatest impact on infectious diseases, surpassing the effect of floods, thunderstorms and windstorms.
The analytics competition was co-sponsored by SAS and Central Michigan University's Institute for Business Insights.
The competition allows students an opportunity to put data mining skills to the test. Team members analyzed weather, population, demographic and hospitalization data to predict which conditions result in more hospitalizations.
UCF competed against 40 teams from 13 colleges and universities to win this year's data mining competition.
"The annual Data Mining Shootout allows students to demonstrate advanced analytical skills. These students were exceptionally creative. The resulting predictive models are valuable to healthcare providers, helping them match the appropriate staffing levels and resources to needs,” said Jerry Oglesby, Senior Director of Education at SAS.
All of the top 25 health plans and pharmaceutical companies depend on SAS Analytics, including solutions such as SAS for health care providers.
"We aimed at developing an early warning system for forecasting diseases," said Jun Han, captain of the UCF team. "The data sets were complicated but, with SAS Analytics at our fingertips, we were well equipped for analytic data preparation, data mining, modeling and reporting. SAS Enterprise Miner helped us improve the accuracy of our predictive models."
Han's team included Chun He, Baiyun Chen, Puwei Chen, Lei Zhang, Junan Miao and Zhixing Chen.
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