DFKI-LT - KEMM: A Knowledge Engineering Methodology in the Medical Domain

Pinar Wennerberg, Sonja Zillner, Manuel Möller, Paul Buitelaar, Michael Sintek
KEMM: A Knowledge Engineering Methodology in the Medical Domain
in: Carola Eschenbach, Michael Gruninger (eds.):
2 5th International Conference on Formal Ontology in Information Systems volume 183,
Frontiers in Artificial Intelligence and Applications, Saarbrücken, Germany, IOS Press, Amsterdam, 2008

Medical research and clinical practice deal with complex and heterogeneous data. This requires a systematic approach for semantic integration of information to support clinicians in their daily tasks. As the clinicians speak and think in a very different language than that of the computer scientists, existing knowledge engineering approaches based on classical expert interviews fall short. Moreover, as human health is a very sensitive subject, the reuse of standardized hence reliable ontologies as medical knowledge resources becomes a key requirement. In this paper, we first discuss the specific medical knowledge engineering requirements, we identified along a semantic medical image and text retrieval use case. Then we report on ongoing work towards establishing a corresponding methodology based on ontology reuse that is derived from the requirements. The methodology, which will be discussed in detail, relies on a novel technique for semi-automatically generating a set of potential user queries to support the knowledge elicitation process.
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