A rule-based disease diagnostic system using a temporal relationship model

Chien Chih Wang, Ming Nan Chien, Chua Huang, Li Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

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 ternporal 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.

Original languageEnglish
Title of host publicationProceedings - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Pages109-115
Number of pages7
Volume4
DOIs
Publication statusPublished - 2007
Event4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007 - Haikou, China
Duration: Aug 24 2007Aug 27 2007

Conference

Conference4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
CountryChina
CityHaikou
Period8/24/078/27/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Applied Mathematics
  • Theoretical Computer Science

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