A computer system for the assistance of syndrome diagnosis in dysmorphology (EL BUSCA) was developed, and used to test the mechanics of the diagnostic process. EL BUSCA has a reference file (REF) with 200 syndromes, expressed in 175 signals. Signals have a weight value resulting from the difference between the number of syndromes including that sign and the total number of syndromes in the REF. A mean signal weight was calculated for each syndrome. The system was tested with 200 published cases (CASES), representing 82 different syndromes. Each consultation (CONS) entered up to 15 patient signals. The system then selected syndromes having three or more of those signals. 'Present' (REF+CASE), 'Absent' (REF only), and 'Additional' (CASE only) signals, as well as the score given by the sum of the weights of 'present' signals, were displayed for each suggested diagnosis. A consultation was successful (positive answer) if the correct diagnosis appeared among the first 12 ranked. EL BUSCA gave a positive answer in 82% of the 200 test consultations. Linear regression, with ranking of the correct diagnosis among the answers as the dependent variable, was used for the analysis of the following results. For the REF, no relationship was found for either the number or the mean weight of the signals with the ranking of the correct diagnosis. For the CASES, there was a linear relationship between the number of signals of each consultation and the ranking of the correct diagnosis, indicating that the larger the number of signals consulted, the lower the ranking of the correct diagnosis. No effect was seen for the mean weight of consulted signals.(ABSTRACT TRUNCATED AT 250 WORDS)
[1]
D F Schorderet,et al.
Diagnosing human malformation patterns with a microcomputer: evaluation of two different algorithms.
,
1987,
American journal of medical genetics.
[2]
R M Winter,et al.
A computerised data base for the diagnosis of rare dysmorphic syndromes.
,
1984,
Journal of medical genetics.
[3]
D Schorderet,et al.
SYNDROC: microcomputer based differential diagnosis of malformation patterns.
,
1985,
Archives of disease in childhood.
[4]
D M Eddy,et al.
The art of diagnosis: solving the clinicopathological exercise.
,
1982,
The New England journal of medicine.
[5]
J Gouvernet,et al.
GENDIAG: A Computer-assisted Facility in Medical Genetics Based on Belief Functions
,
1985,
Methods of Information in Medicine.
[6]
H. E. Pople,et al.
Internist-I, an Experimental Computer-Based Diagnostic Consultant for General Internal Medicine
,
1982
.
[7]
D. Hunter.
The art of diagnosis.
,
1955,
The Central African journal of medicine.