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A Rule-Based Disease Diagnostic System Using a Temporal Relationship Model

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4 Author(s)

We use a temporal model to express temporal relationships among diseases that may have mutual affect potentially. The temporal model defines six types of relationships: before, after, contained, contains, start-overlap, and end-overlap. First, the temporal relationship between diseases of each patient is searched, and then, the temporal relationships of all patients are analyzed to determine the correlation of these diseases. The timestamped diagnostic data are built as facts and the physician specified rules of diseases are built as inference rules of the inference engine. The temporal relationship model is implemented as a rule based system using the Java based expert system, Jess. The rules for determining disease diagnoses and temporal relationships are written as text files and are input to the system. The major goal of this paper is to provide a system kernel for applications of medical diagnosis system.

Published in:

Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on  (Volume:4 )

Date of Conference:

24-27 Aug. 2007