An Intelligent Disease Diagnosis System by Fuzzy Similarity Distance
The progress of Artificial intelligence and Information technology has been driving research of intelligent diagnosing, and the efficiency of diagnosis is improved by disease diagnosing system .In this paper, we analyze the comparability and relativity between fuzzy similarity distance and disease diagnosis, and initiate the theoretical model of fuzzy-distance on the basis of fuzzy membership factors vectors, and some corresponding data structure. In addition, the inference algorithm and the hierarchy of system are brought forward. Experimentation statistics demonstrate that the novel diagnosis system could obtain a satisfying accuracy rate of diagnosis, and low a rate of misdiagnosis effectively.
Dongye Sun, Wen-Pei Sung and Ran Chen
W. X. Tan et al., "An Intelligent Disease Diagnosis System by Fuzzy Similarity Distance", Applied Mechanics and Materials, Vols. 71-78, pp. 2218-2221, 2011