The Evidential Reasoning Approach to Medical Diagnosis using Intuitionistic Fuzzy Dempster-Shafer Theory

• Main Authors: Yanni Wang, Yaping Dai, Yu-wang Chen, Fancheng Meng
• Format: Article
• Language: English
• Published: Atlantis Press 2015-01-01
• Series: International Journal of Computational Intelligence Systems
• Subjects: Fuzzy sets; evidential reasoning; uncertainty; Dempster-Shafer theory; inclusion measure; medical diagnosis
• Online Access: https://www.atlantis-press.com/article/25868584.pdf

For medical diagnosis, fuzzy Dempster-Shafer theory is extended to model domain knowledge under probabilistic and fuzzy uncertainty. However, there are some information loss using discrete fuzzy sets and traditional matching degree method. This study aims to provide a new evidential structure to reduce information loss. This paper proposes a new intuitionistic fuzzy evidential reasoning (IFER) approach which combines intuitionistic trapezoidal fuzzy numbers and inclusion measure to improve the accuracy of representation and reasoning. The proposed approach has been validated by a stroke diagnosis. It is shown that the IFER approach leads to more accurate results.