- EXPERT SYSTEMS WITH APPLICATIONS Journal
- March 2010
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Medical differential diagnosis (ddx) is based on the estimation of multiple distinct parameters in order to determine the most probable diagnosis. Building an intelligent medical differential diagnosis system
implies using a number of knowledge-based technologies which avoid
ambiguity, such as ontologies representing specific structured
information, but also strategies such as computation of probabilities of
various factors and logical inference, whose combination outperforms
similar approaches. This paper presents ODDIN, an ontology-driven
medical diagnosis system which applies the aforementioned strategies.
The architecture and proof-of-concept implementation is described, and
results of the evaluation are discussed.