Computer-Assisted Bayesian Diagnosis of Connective Tissue Diseases - Walsh, T. R.; Lindberg, D. A. B.; Klink, E. J., Jr.; Sharp, G. C. (Methods of Information in Medicine, 1981)
Bayes’ Theorem was applied interactively with a microcomputer to a rheumatology data base to provide a differential diagnosis of six primary connective tissue diseases. This diagnosis was evaluated in terms of the clinical diagnosis reached by a consensus of at least two of three rheumatologists. For each patient case, the diagnosis having the highest likelihood, after taking into account disease prevalence and combined symptom frequencies, was selected by the computer. The diagnostic model was trained by data from thoroughly studied clinical cases, for each of which 44 clinical and laboratory findings were collected according to a standard data base protocol. Each case received one of six diagnoses based on full clinical appraisal. Comparison of the diagnoses revealed 100 per cent agreement between the computer and the clinicians for the training population of 137 cases, and 94.4 per cent agreement for an independent, thoroughly studied test set of 89 cases. During testing, we observed the system had a genuine educational value for medical students and non-rheumatologists. In addition, there appeared to be a potential future use in facilitating actual clinical problem solving.
Keywords: Microcomputer; Computer-aided Diagnosis; Bayes Theorem; Rheumatology