Abstract
Knowledge about human anatomy, radiology and diseases that is essential
for medical images can be acquired from medical ontology terms and
relations. These can then be analyzed using domain corpora to observe
statistically most relevant term-relation-term patterns. We argue
that such patterns are the basis for more complex clinical search
queries and describe our approach for deriving them. These patterns
can then be used to support the knowledge elicitation process between
the domain expert and the knowledge engineer by providing a common
vocabulary for the communication.
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