DECISION-SUPPORT FOR PSYCHIATRIC-DIAGNOSIS BASED ON A SIMPLE QUESTIONNAIRE

This paper compares two classifiers: Pseudo Bayesian and Neural Networ k for assisting in making diagnoses of psychiatric patients based on a simple yes/no questionnaire which is provided at the outpatient's fir st visit to the hospital. The classifiers categorize patients into thr ee most commonly seen ICD classes, i.e. schizophrenic, emotional and n eurotic disorders. One hundred completed questionnaires were utilized for constructing and evaluating the classifiers. Average correct decis ion rates were 73.3% for the Pseudo Bayesian Classifier and 77.3% for the Neural Network classifier. These rates were higher than the rate w hich an experienced psychiatrist achieved based on the same restricted data as the classifiers utilized. These classifiers may be effectivel y utilized for assisting psychiatrists in making their final diagnoses .