Using decision fusion methods to improve outbreak detection in disease surveillance

Using decision fusion methods to improve outbreak detection in disease surveillance

Abstract Background When outbreak detection algorithms (ODAs) are considered individually, the task of outbreak detection can be seen as a classification problem and the ODA as a sensor providing a binary decision (outbreak yes or no) for each day of surveillance. When they are considered jointly (i...

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Bibliographic Details
Main Authors: Gaëtan Texier, Rodrigue S. Allodji, Loty Diop, Jean-Baptiste Meynard, Liliane Pellegrin, Hervé Chaudet
Format: Article
Language:English
Published: BMC 2019-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Decision support system
Disease surveillance system
Decision making
Decision fusion
Outbreak detection
Bayesian network
Online Access:http://link.springer.com/article/10.1186/s12911-019-0774-3

Internet

http://link.springer.com/article/10.1186/s12911-019-0774-3

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