Abstract
We have developed an OtoNeurological Expert system (ONE) to aid the diagnostics of vertigo, to assist teaching and to implement the database for research. The database contains detailed information on the patient history, signs and test results necessary for the diagnostic work with vertiginous patients. The pattern recognition method was used in the reasoning process. Questions regarding symptoms, signs and test results are weighted and scored for each disease, and the most likely disease is recognized from the defined disease profiles. Uncertainties in reasoning, caused by missing information, were solved with a method resembling fuzzy logic. We have also applied adaptive computer applications, such as genetic algorithms and decision trees, in the reasoning process. In the validation the expert system ONE proved to be a sound decision maker, by solving 65% of the cases correctly, while the physicians' mean was 69%. To improve the expert system ONE further, a follow-up should be implemented for the patients, to ease the diagnostic work of some difficult diseases. The six diseases were detected with high accuracy also with adaptive learning methods and discriminant analysis. An expert system is a practical tool in otoneurology. We aim to construct a hybrid program for the reasoning, where the best reasoning method for each disease is used.