Improvement in the computer-assisted diagnosis of cerebral tumours

Most applications of Bayes theorem in computer-aided diagnosis have been to situations involving the differential diagnosis of a small list of disease categories. In the case of the diagnosis of cerebral tumours, if each tumour type in each main anatomical situation is counted as a single diagnosis, there are about 100 possible disease categories. This paper investigates a method of incorporating expert prior information into the computer-aided diagnosis process so that this large number of categories can be handled.