A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance

Monitoring the development of infectious diseases is of great importance for the prevention of major outbreaks. Syndromic surveillance aims at developing algorithms which can detect outbreaks as early as possible by monitoring data sources which allow to capture the occurrences of a certain disease....

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Bibliographic Details

Main Authors:	Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Format:	Artigo
Language:	Inglês
Published:	MDPI AG 2021-03-01
Series:	Computers
Subjects:	syndromic surveillance outbreak detection multivariate surveillance anomaly detection
Online Access:	https://www.mdpi.com/2073-431X/10/3/32
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