Volume 8, Issue 1, January 2015, Pages 75 - 94
The Evidential Reasoning Approach to Medical Diagnosis using Intuitionistic Fuzzy Dempster-Shafer Theory
Yanni Wang, Yaping Dai, Yu-wang Chen, Fancheng Meng
Received 9 March 2014, Accepted 17 June 2014, Available Online 1 January 2015.
- https://doi.org/10.2991/ijcis.2015.8.1.7How to use a DOI?
- Fuzzy sets, evidential reasoning, uncertainty, Dempster-Shafer theory, inclusion measure, medical diagnosis
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Yanni Wang AU - Yaping Dai AU - Yu-wang Chen AU - Fancheng Meng PY - 2015 DA - 2015/01/01 TI - The Evidential Reasoning Approach to Medical Diagnosis using Intuitionistic Fuzzy Dempster-Shafer Theory JO - International Journal of Computational Intelligence Systems SP - 75 EP - 94 VL - 8 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2015.8.1.7 DO - https://doi.org/10.2991/ijcis.2015.8.1.7 ID - Wang2015 ER -