Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance

We investigate the use of Twitter data to deliver signals for syndromic surveillance in order to assess its ability to augment existing syndromic surveillance efforts and give a better understanding of symptomatic people who do not seek healthcare advice directly. We focus on a specific syndrome—ast...

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Udgivet i:PLoS One
Main Authors: Edo-Osagie, Oduwa, Smith, Gillian, Lake, Iain, Edeghere, Obaghe, De La Iglesia, Beatriz
Format: Artigo
Sprog:Inglês
Udgivet: Public Library of Science 2019
Fag:
Research Article
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6638773/
https://ncbi.nlm.nih.gov/pubmed/31318885
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0210689
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