TY - GEN
T1 - Modeling a fuzzy rule based expert system combining positive and negative knowledge for medical consultations using the importance of symptoms
AU - Nu, Mai Thi
AU - Phuong, Nguyen Hoang
AU - Hirota, K.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/30
Y1 - 2017/8/30
N2 - The paper is to present an approach to including the importance of symptoms to a fuzzy rule based expert system combining positive and negative knowledge for medical consultations. We describe the rule base consisting of positive fuzzy rule for confirmation of conclusion and negative fuzzy rules for exclusion of conclusion with degrees of importance of symptoms. We also propose extend Max-Min inference systems by adding t-norm for calculating degrees of importance of symptoms. To combining positive and negative knowledge, an ordered Albelian group operation is applied. Based on this approach, the system can adapt more with real clinical application of medical consultation. Some examples to show the advantage of this approach are presented.
AB - The paper is to present an approach to including the importance of symptoms to a fuzzy rule based expert system combining positive and negative knowledge for medical consultations. We describe the rule base consisting of positive fuzzy rule for confirmation of conclusion and negative fuzzy rules for exclusion of conclusion with degrees of importance of symptoms. We also propose extend Max-Min inference systems by adding t-norm for calculating degrees of importance of symptoms. To combining positive and negative knowledge, an ordered Albelian group operation is applied. Based on this approach, the system can adapt more with real clinical application of medical consultation. Some examples to show the advantage of this approach are presented.
KW - fuzzy rule based expert systems
KW - positive and negative knowledge
KW - the importance of symptoms
UR - http://www.scopus.com/inward/record.url?scp=85030840762&partnerID=8YFLogxK
U2 - 10.1109/IFSA-SCIS.2017.8023266
DO - 10.1109/IFSA-SCIS.2017.8023266
M3 - Conference contribution
AN - SCOPUS:85030840762
T3 - IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
BT - IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th Joint World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, IFSA-SCIS 2017
Y2 - 27 June 2017 through 30 June 2017
ER -