Use of Description Logic Classificatio Penetrating

The consequences of penetrating injuries can be com-plex, including abnormal blood flow through the injury channel and functional impairment of organs if arter-ies supplying them have been severed. Determining the consequences of such injuries can be posed as a clas-sification problem, requiring a priori symbolic knowl-edge 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 capabili-ties of automated classification using the Web Ontol-ogy Language (OWL) to reason about the conse-quences of penetrating injuries. We created in OWL a knowledge model of chest and heart anatomy describ-ing 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 inju-ries. 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