Quantifying the determinants of outbreak detection performance through simulation and machine learning

Author:

Jafarpour Nastaran,Izadi Masoumeh,Precup Doina,Buckeridge David L.

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference30 articles.

1. A simulation study comparing aberration detection algorithms for syndromic surveillance;Jackson;BMC Med Inform Decis Mak,2007

2. Approaches to the evaluation of outbreak detection methods;Watkins;BMC Public Health,2006

3. Buckeridge DL, Okhmatovskaia A, Tu S, O’Connor M, Nyulas C, Musen MA. Predicting outbreak detection in public health surveillance: quantitative analysis to enable evidence-based method selection. In: AMIA annual symposium proceedings: American medical informatics association; 2008. p. 76.

4. Izadi M, Buckeridge D, Okhmatovskaia A, Tu SW, O‘Connor MJ, Nyulas C, et al. A Bayesian network model for analysis of detection performance in surveillance systems. In: AMIA annual symposium proceedings: American medical informatics association; 2009. p. 276.

5. The bioterrorism preparedness and response early aberration reporting system (EARS);Hutwagner;J Urban Health,2003

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