id: 02180349
dt: j
an: 02180349
au: Tsumoto, Shusaku
ti: Knowledge discovery in clinical databases and evaluation of discovered
    knowledge in outpatient clinic.
so: Inf. Sci. 124, No. 1-4, 125-137 (2000).
py: 2000
pu: Elsevier Science Inc. (North-Holland), New York, NY
la: EN
cc: H.2.8 I.2.1 J.3
ut: knowledge discovery in clinical databases; rule induction; rough sets;
    expert system; differential diagnosis; congenital disorders
ci: 
li: doi:10.1016/S0020-0255(99)00065-1
ab: Summary: Rule induction methods have been proposed in order to discover
    knowledge automatically from databases. However, conventional
    approaches do not focus on the implementation of induced results into
    an expert system. In the paper, the author focuses not only on rule
    induction but also on its evaluation and presents a systematic approach
    from the former to the latter as follows. First, a rule induction
    system based on rough sets and attribute-oriented generalization is
    introduced and was applied to a database of congenital malformation to
    extract diagnostic rules. Then, by the use of the induced knowledge, an
    expert system which makes a differential diagnosis on congenital
    disorders is developed. Finally, this expert system was evaluated in an
    outpatient clinic, the results of which show not only that the system
    performs as well as a medical expert, but also that the system is very
    useful for instruction to medical residents.
rv: