Academic Journal
Prediction of Peaks of Seasonal Influenza in Military Health-Care Data.
| Taitara: | Prediction of Peaks of Seasonal Influenza in Military Health-Care Data. |
|---|---|
| Ngā kaituhi: | Buczak, Anna L., Baugher, Benjamin, Guven, Erhan, Moniz, Linda, Babin, Steven M., Chretien, Jean-Paul |
| Puna: | Biomedical Engineering & Computational Biology; 2016 Supplement 2, Vol. 7, p15-26, 12p |
| Whakarāpopotonga: | Influenza is a highly contagious disease that causes seasonal epidemics with significant morbidity and mortality. The ability to predict influenza peak several weeks in advance would allow for timely preventive public health planning and interventions to be used to mitigate these outbreaks. Because influenza may also impact the operational readiness of active duty personnel, the US military places a high priority on surveillance and preparedness for seasonal outbreaks. A method for creating models for predicting peak influenza visits per total health-care visits (ie, activity) weeks in advance has been developed using advanced data mining techniques on disparate epidemiological and environmental data. The model results are presented and compared with those of other popular data mining classifiers. By rigorously testing the model on data not used in its development, it is shown that this technique can predict the week of highest influenza activity for a specific region with overall better accuracy than other methods examined in this article. [ABSTRACT FROM AUTHOR] |
| Ngā kupu marau: | INFLUENZA, PUBLIC health, DATA mining, MEDICAL care, FUZZY logic, ASSOCIATION rule mining |
| Copyright of Biomedical Engineering & Computational Biology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| ISSN: | 11795972 |
| DOI: | 10.4137/BECB.S36277 |
| Pātengi raraunga: | Complementary Index |