Abstract

The consequences of penetrating injuries can be complex, including abnormal blood flow through the injury channel and functional impairment of organs if arteries supplying them have been severed. Determining the consequences of such injuries can be posed as a classification problem, requiring a priori symbolic knowledge of anatomy. We hypothesize that such symbolic knowledge can be modeled using ontologies, and that the reasoning task can be accomplished using knowl-edge representation in description logics (DL) and automatic classification. We demonstrate the capabilities of automated classification using the Web Ontology Language (OWL) to reason about the consequences of penetrating injuries. We created in OWL a knowledge model of chest and heart anatomy describing the heart structure and the surrounding anatomic compartments, as well as the perfusion of regions of the heart by branches of the coronary arteries. We then used a domain-independent classifier to infer ischemic regions of the heart as well as anatomic spaces containing ectopic blood secondary to the injuries. Our results highlight the advantages of posing reasoning problems as a classification task, and lever-aging the automatic classification capabilities of DL to create intelligent applications.

View details for PubMedID 16779120