USE OF A BAYESIAN ALGORITHM IN THE COMPUTER-ASSISTED DIAGNOSIS OF APPENDICITIS

  • 1 January 1984
    • journal article
    • research article
    • Vol. 158  (3) , 219-222
Abstract
Patients (100) with acute right lower quadrant abdominal pain were prospectively evaluated with a computerized Bayesian diagnostic algorithm. An accurary rate of 92% was obtained. Computer recommendations would have resulted in a negative exploration rate of 9%, compared with the rate of 19% which was actually obtained. Even though clinical management of these patients was in keeping with accepted standards, the Bayesian program would have avoided 8 unnecessary operations. In all instances in which the patient presented with appendicitis, the computer correctly predicted that appendicitis was present. Computer-assisted diagnostic programs using a Bayesian approach may have some role in the evaluation of right lower quadrant abdominal pain. The technique presented describes a means of developing a database of conditional probabilities without reliance on large patient surveys. Even with this refinement, the Bayesian approach to diagnosis remains complex. The development of this type of program requires close interaction between computer scientists and surgeons. The approach does appear promising and it may well be worth the considerable effort required to initiate such a system. The exact role for Bayesian diagnostic analysis cannot be predicted at this point. It should have no greater importance than a routine laboratory test. Perhaps the results of Bayesian analysis in this setting might assume a diagnostic significance similar to that of the white blood cell count.

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