Machine learning and data mining for epidemic surveillance

Medical Journal of Australia

Volumn 196, Issue 5, 2012, Pages 301-

  Kofod Petersen, Anders ^a,b  

^a SINTEF   (Norway)

^b NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

2009 H1N1 INFLUENZA; ACCESS TO INFORMATION; ALGORITHM; ARTICLE; COMMUNICABLE DISEASE; COMPUTER PROGRAM; DATA MINING; DISEASE ACTIVITY; DISEASE CONTROL; DISEASE SURVEILLANCE; EPIDEMIC; EPIDEMIOLOGY; HUMAN; KNOWLEDGE; MACHINE LEARNING; MASS MEDIUM; MATHEMATICAL COMPUTING; MEDICAL INFORMATION SYSTEM; ONLINE SYSTEM; PREDICTION; PROBABILITY;

ARTIFICIAL INTELLIGENCE; BLOGGING; DATA MINING; EPIDEMICS; EPIDEMIOLOGIC RESEARCH DESIGN; HUMANS; POPULATION SURVEILLANCE; SOCIAL MEDIA;

EID: 84859132420     PISSN: 0025729X     EISSN: 13265377     Source Type: Journal    
DOI: 10.5694/mja12.10283     Document Type: Article

References (4)

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3. Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the US during the Influenza A H1N1 Pandemic. PLoS One 2011; 6: e19467.
4. Ginsberg J, Mohebbi MH, Patel RS, et al. Detecting influenza epidemics using search engine query data. Nature 2009; 457: 1012-1014.