The knowledge construction was
based on a concept of production rules, which was
performed in tree structure. The inference engine
used interactive forward chaining technique to infer a
diagnostic result. The proposed system was designed
to interact with user by using question forms of symp-
toms, and it was able to support text and picture in-
formation. The architecture of this system consisted
of inference engine, knowledge base, user interface
unit, knowledge acquisition unit, explanation mod-
ule and blackboard. This medical knowledge-based
system was developed by Borland c
++ language on
Windows XP system. Finally this system was applied
to check accuracy by comparing with general physi-
cian’s diagnoses. The experimental result showed the
diagnosis of the system more than 97% accurately at
the 0.01 level of significance, when it is compared with
diagnosis of a physician.