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- | The CVDI IAB members nominated two technological breakthroughs for their organizations that are expected to be included in the 2016 I/UCRC Breakthrough Compendium. | ||
- | ===== Flu Prediction Model ===== | + | In 2012, CVDI pioneered the Big Data revolution, and 10 years later has grown into a model National Science Foundation IUCRC center. |
- | {{ :about:cvdi-fio-visualization-snapshot3.jpeg? | + | * **Big Data Pioneers** |
+ | * **Six Partners Strong** | ||
+ | * One of only 25 NSF CISE Centers in the US | ||
+ | * **International Presence** - The addition of Tampere University in Finland to CVDI marks only a handful of IUCRCs in the country with an international research site | ||
+ | * **Innovating the South** - CVDI is the first IUCRC Center in Louisiana | ||
+ | ===== Technological Breakthroughs ===== | ||
+ | Industry members nominated two technological breakthroughs for their organizations that are expected to be included in the 2016 I/UCRC Breakthrough Compendium. | ||
+ | ==== Flu Prediction Model ==== | ||
+ | {{ : | ||
+ | The influenza forecasting model developed by Dr. Raju Gottumukkala uses a two-stage vectorized time series model that captures the influence of local environmental weather conditions and historical flu spread patterns to improve the flu prediction model. This is helpful for organizations like Schumacher Clinical Partners to forecast emergency department patient visits during peak flu season. | ||
+ | ==== Hotspot Prediction Model ==== | ||
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- | The influenza forecasting model developed by Dr. Raju Gottumukkala uses a two-stage vectorized time series model that captures the influence of local environmental weather conditions and historical flu spread patterns to improve the flu prediction model. This is helpful for organizations like Schumacher Clinical Partners to forecast emergency department patient visits during peak flu season. | ||
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- | ===== Hotspot Prediction Model ===== | ||
The hotspot prediction technique developed by Dr. Jian Chen uses an ensemble approach that leverages multiple models to predict hotspot evolution outcomes that had a significant reduction in false positives. This is helpful for organizations like CGI Federal for both understanding infectious disease hotspots and crime hotspots. | The hotspot prediction technique developed by Dr. Jian Chen uses an ensemble approach that leverages multiple models to predict hotspot evolution outcomes that had a significant reduction in false positives. This is helpful for organizations like CGI Federal for both understanding infectious disease hotspots and crime hotspots. |