An expert system on the diagnosis of ascites.
We constructed an expert system on the diagnosis of ascites, using a combination of case reports and unpublished patient data. Rule production was by induction from examples, and the program operated on an algorithm which was a modification of Quinlan's ID3. The result was a small, but formally complete expert system. When tested against a new data set of patients, our expert system predicted the clinical diagnosis 82% of the time.
Kinney
E L
EL
Cardiology Division, University of Miami School of Medicine, Florida 33101.
Brafman
D
D
Wright
R J
RJ
D001201:Ascites / Q000175:diagnosis* / Q000209:etiology; D003936:Diagnosis, Computer-Assisted; D005103:Expert Systems; D006801:Humans; D008838:Microcomputers; D012986:Software Validation