ODDIN: Ontology-Driven Differential Diagnosis based on Logical Inference and Probabilistic Refinements Articles uri icon

authors

publication date

  • March 2010

start page

  • 2621

end page

  • 2628

issue

  • 3

volume

  • 37

International Standard Serial Number (ISSN)

  • 0957-4174

Electronic International Standard Serial Number (EISSN)

  • 1873-6793

abstract

  • 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.