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During the last 20 years, Danish gastroenterologists and biostatisticians have been involved in practical and theoretical research aimed at providing computer-assisted decision support in clinical practice. On the practical side, we summarize two clinical applications, one in the acute abdomen, the other in jaundice. The former project is part of a worldwide effort which appears able to reduce considerably the perforated appendix rate and the negative laparotomy rate. In the latter project, also entwined in international activities, three methods of early statistical discrimination of jaundice causes have been tested, and it has been shown how ultrasonographic data can be incorporated into the diagnostic assessment. On the theoretical side, a Dutch-Danish group has been looking into how one best designs a trial and analyses its data in the context of measuring the quality and impact of machine-made diagnostic advice. Having pointed out the international ramifications of these activities, we outline what may lie ahead: Gastroenterologists must be prepared to join large-scale field trials of clinical advice-giving software. In the future, however, such software will often become embedded in general hospital recordkeeping systems.

Extensive clinical and clinical chemical information was collected from 1002 consecutive jaundiced patients. Initial selection of variables based on Chi 2-tests or Mann-Whitney U-test allowed the removal of 64 of the 107 variables originally collected. A further selection of variables was carried out using a modified version of Bayes' rule thus reducing the number of variables from 43 to 22. Of the 982 patients with a final diagnosis 743 patients (76%) could be classified correctly into one of 13 diagnostic categories. The Bayes' rule was also applied to a test group of a further 110 jaundiced patients and found to perform equally well: of 108 patients with a final diagnosis 81 (75%) were correctly classified. A comparison between the clinician's diagnosis and the computer-aided diagnosis according to Bayes' rule demonstrated agreement with regard to one of the 13 diagnostic alternatives in 734 patients (75%), of whom 81 patients were wrongly diagnosed. In the test group agreement upon diagnosis was found in 80 patients (74%). By plausibly combining the computer-aided and the clinician's preliminary diagnoses, more correct classifications were obtained than with either method alone. Many diagnostic modalities such as ultrasound examination, CT-scan, and direct cholangiography are at hand today for the differential diagnosis of jaundice. Computer-aided diagnosis using Bayes' rule has proved a reliable tool for the clinician and can be used in the planning of a diagnostic strategy for the individual jaundiced patient.