tetano
Editor, Senior Moderator
Biomed Eng Comput Biol. 2016 Apr 19;7(Suppl 2):15-26. doi: 10.4137/BECB.S36277. eCollection 2016.
[h=1]Prediction of Peaks of Seasonal Influenza in Military Health-Care Data.[/h] Buczak AL[SUP]1[/SUP], Baugher B[SUP]1[/SUP], Guven E[SUP]1[/SUP], Moniz L[SUP]1[/SUP], Babin SM[SUP]1[/SUP], Chretien JP[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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.
[h=4]KEYWORDS:[/h] association rule mining; fuzzy logic; influenza; prediction; predictor variables
PMID: 27127415 [PubMed] PMCID: PMC4838055 Free PMC Article
[h=1]Prediction of Peaks of Seasonal Influenza in Military Health-Care Data.[/h] Buczak AL[SUP]1[/SUP], Baugher B[SUP]1[/SUP], Guven E[SUP]1[/SUP], Moniz L[SUP]1[/SUP], Babin SM[SUP]1[/SUP], Chretien JP[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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.
[h=4]KEYWORDS:[/h] association rule mining; fuzzy logic; influenza; prediction; predictor variables
PMID: 27127415 [PubMed] PMCID: PMC4838055 Free PMC Article