DocumentCode :
604523
Title :
Reasoning research on vague information based on case-based reasoning and fuzzy-based reasoning in traditional Chinese medicine diagnosis
Author :
Feng Yang ; Hemin Jin ; Huimin Qi
Author_Institution :
Inst. of Inf. Technol., Henan Univ. of TCM, Zhengzhou, China
fYear :
2012
fDate :
29-31 Dec. 2012
Firstpage :
1813
Lastpage :
1817
Abstract :
There is a lot of vague information about TCM (Traditional Chinese Medicine) diagnosis difficult to understand through computer. Reasoning process, by coalescing of the CBR (Case-based Reasoning) and FBR (Fuzz-based Reasoning) in artificial intelligence, makes up for shortcomings of their alone, can achieve a good understanding of information in TCM diagnosis. As for the new diagnostic features, the reasoning algorithm firstly finds them in the existing case base, if fails, fuzzy reasoning mechanism will start automatically, then ultimately the credible results will be presented to the user. Facts have shown that the algorithm has good reasoning ability and can get more accurate diagnoses.
Keywords :
case-based reasoning; fuzzy reasoning; medical diagnostic computing; CBR; FBR; TCM diagnosis; artificial intelligence; case-based reasoning; fuzzy reasoning mechanism; fuzzy-based reasoning; reasoning ability; reasoning algorithm; traditional Chinese medicine diagnosis; vague information; CBR; FBR; Matching degree; Membership; TCM diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
Type :
conf
DOI :
10.1109/ICCSNT.2012.6526271
Filename :
6526271
Link To Document :
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