Limits to diagnostic accuracy.
This paper explores the limits to computer-aided medical diagnosis. A specific application area (the diagnosis of abdominal pain of suspected gynaecological origin) is chosen, and the factors limiting the accuracy of computer programs are investigated by means of a simulation model which has been shown previously to generate realistic cases. The model is used to generate arbitrarily large training and test sets. The results suggest that, while statistical dependencies exist amongst symptoms and signs, there is little to be gained by taking interactions into account. However, failure to record all possible observations does limit diagnostic accuracy significantly. The results suggest that near-optimal diagnostic accuracy (75-80%) can be obtained with a training set size of 10(5) cases simply by applying Bayes' theorem with the usual assumption of conditional independence.
Todd
B S
BS
Programming Research Group, Oxford University Computing Laboratory, UK.
Stamper
R
R
D015746:Abdominal Pain / Q000209:etiology; D001499:Bayes Theorem; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000706:statistics & numerical data; D005260:Female; D005831:Genital Diseases, Female / Q000150:complications / Q000175:diagnosis; D006801:Humans; D008954:Models, Biological; D012680:Sensitivity and Specificity