Chief complaints are often represented textually and as a mixture of complex and context-dependant lexical symbols with little formal sentence structure. Although human experts usually comprehend this information in its right context intuitively and effortlessly, use of chief complaint data by computers is a challenge. Semantic approaches for text understanding are concerned with the meaning of terms and their relationships, driven from an explicit model rather than their syntactic forms. Explicit representation of domain concepts along with computer reasoning enables a knowledgeable computer agent to identify those concepts in a given text and pinpoint relevant relationships if they make sense according to an existing formal model available to the agent .
Objective
This paper proposes a semantic approach to processing free form text information such as chief complaints using formal knowledge representation and Description Logic reasoning. Our methods extract concepts and as much contextual information as is available in the text. Output consists of a computationally interpretable representation of this information using the Resource Definition Framework (RDF) and UMLS Metathesaurus.