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about:recognition [2021/03/04 14:57] andrea.frey [Flu Prediction Model] |
about:recognition [2021/06/24 14:44] andrea.frey |
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- | In 2012, CVDI pioneered the Big Data revolution | + | |
+ | In 2012, CVDI pioneered the Big Data revolution | ||
* Only IUCRC with “Visualization & Big Data Analytics” focus | * Only IUCRC with “Visualization & Big Data Analytics” focus | ||
- | * Jointly created by UL Lafayette & Drexel | + | * Created a strong research network beginning with UL Lafayette & Drexel |
* One of only 25 NSF CISE Centers in the US | * One of only 25 NSF CISE Centers in the US | ||
- | * One of six IUCRCs | + | * The addition |
===== Technological Breakthroughs ===== | ===== Technological Breakthroughs ===== | ||
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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. | 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 ===== | + | ==== 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. |