In an increasingly globalised world, where infectious disease outbreaks can rapidly circulate through the international transport system, and the threat of bioterrorism is constant, there is a need to develop reusable resources to support early-stage disease outbreak detection. This paper presents the Extended Syndromic Surveillance Ontology (ESSO), an open source terminological ontology designed to facilitate the mining of free-text clinical documents in English to support timely disease outbreak surveillance. ESSO consists of 279 clinical concepts (Fever, Slurred Speech, Diplopia, and so on) across eight syndromes (respiratory syndrome, constitutional syndrome, and so on) and is enriched with regular expressions to support concept identification in text. The ontology is shown to have good coverage in the target domain.
|Number of pages||8|
|Journal||CEUR Workshop Proceedings|
|State||Published - 2010|
|Event||3rd International Workshop on Health Document Text Mining and Information Analysis 2011, LOUHI 2011 - Bled, Slovenia|
Duration: Jul 6 2011 → Jul 6 2011
- Natural language processing
- Syndromic surveillance