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Approach to combining case based reasoning with rule based reasoning for lung disease diagnosis

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4 Author(s)
Nguyen Hoang Phuong ; The Rio Grande Inst. for Soft Comput., New Mexico State Univ., Las Cruces, NM, USA ; N. R. Prasad ; Dang Huu Hung ; J. T. Drake

In recent years, we have developed an expert system for the diagnosis of lung diseases using cased-based reasoning and other rule-based systems using fuzzy logic. Case-based reasoning is the process of using solutions to previously encountered problems as a basis for reasoning solution to new problems. The knowledge base of the Case-Based Reasoning System for Diagnosis of Lung Diseases is a case base of patient records consisting of documented experience. On the other hand, the knowledge base of the Expert System for Lung Diseases is a set of IF-THEN rules based on the experience of medical doctors. In fact, these two systems make diagnoses of lung diseases based on two different knowledge bases. One is a case base and other is a rule base. Our design combines the diagnoses of these two methods in order to obtain improved accuracy in lung disease diagnosis. In this paper, we offer an approach to combining case-based reasoning and rule-based reasoning for lung disease diagnosis

Published in:

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th  (Volume:2 )

Date of Conference:

25-28 July 2001