Human versus machine: a comparison of a computer 'expert system' with human experts in the diagnosis of vaginal discharge.

A model system has been designed which generates 'cases' of vaginal discharge. Each such case is presented to a human for diagnosis, and this is then compared with a computer diagnosis using two forms of Bayes' theorem. Six subjects (2 medical; 4 non-medical) participated in the trial and each examined 100 successive 'cases'. When the humans had forewarning of the trial and full access to the knowledge-base their performance was superior to that of Bayes' theorem using positive features only and equivalent to that using both positive and negative features. When the trial was repeated without forewarning the human performance was markedly inferior to that of the machine. It is concluded: that human and computer-aided diagnosis can be of approximately equal efficiency for complex and non-definitive data; that the imperfections of human memory give an obvious potential advantage to the machine in this type of situation.