Ontologies representing knowledge from the public health and surveillance domains currently exist. However, they focus on infectious diseases (infectious disease ontology), reportable diseases (PHSkbFretired) and internet surveillance from news text (BioCaster ontology), or are commercial products (OntoReason public health ontology). From the perspective of biosurveillance text mining, these ontologies do not adequately represent the kind of knowledge found in clinical reports. Our project aims to fill this gap by developing a stand-alone ontology for the public health/biosurveillance domain, which (1) provides a starting point for standard development, (2) is straightforward for public health professionals to use for text analysis, and (3) can be easily plugged into existing syndromic surveillance systems.
Objective
To develop an application ontology - the extended syndromic surveillance ontology - to support text mining of ER and radiology reports for public health surveillance. The ontology encodes syndromes, diagnoses, symptoms, signs and radiology results relevant to syndromic surveillance (with a special focus on bioterrorism).