Ontology-Based Automatic Chief Complaints Classification for Syndromic Surveillance

This paper presents a novel ontology-based approach to classify free-text chief complaints (CCs) into syndrome categories. This approach exploits the semantic relations in a medical ontology to address the CC word variation problem. Initial computational experiments indicate that this ontology-based approach is able to improve significantly the probability that a CC can be correctly classified as a syndrome.