Objective. AI/RHEUM is a multimedia expert system developed originally to assist in the diagnosis of rheumatic diseases in adults. In the present study we evaluated the usefulness of a modified version of this diagnostic decision support system in diagnosing childhood rheumatic diseases. Methodology. AI/RHEUM was modified by the addition of 5 new diseases to the knowledge base of the system. Criteria tables for each of the diseases included in the knowledge base were modified to suit the needs of children. The modified system was tested on 94 consecutive children seen in a pediatric rheumatology clinic. Results. AI/RHEUM made the correct diagnosis in 92% of the cases when the diagnosis was available in the knowledge base of the system. It was also shown to be effective in the education of pediatric trainees through its multimedia features. Conclusions. AI/RHEUM is an expert system that may be helpful to the nonspecialist as a diagnostic decision support system and as an educational tool.
[1]
D A Lindberg,et al.
Anatomy of a knowledge-based consultant system: AI/RHEUM.
,
1986,
M.D. computing : computers in medical practice.
[2]
Lawrence C. Kingsland,et al.
The Evaluation of Medical Expert Systems: Experience with the AI/RHEUM Knowledge-Based Consultant System in Rheumatology
,
1988
.
[3]
H J Moens,et al.
Development and validation of a computer program using Bayes's theorem to support diagnosis of rheumatic disorders.
,
1992,
Annals of the rheumatic diseases.
[4]
L. Kingsland,et al.
The AI/RHEUM knowledge-based computer consultant system in rheumatology. Performance in the diagnosis of 59 connective tissue disease patients from Japan.
,
1988,
Arthritis and rheumatism.