Neural network based on adaptive resonance theory as compared to experts in suggesting treatment for schizophrenic and unipolar depressed in-patients

Abstract

A modified neural network based on adaptive resonance theory (ART) was trained with the records of 211 psychiatric inpatients (74 schizophrenic, 50 unipolar depressed, 34 bipolar depressed, 20 bipolar manic, 33 other) who improved by at least 40 points on the GAFS during 8 weeks of treatment. Thereafter, a comparison was made between the clinical response of another 26 schizophrenic patients and 28 unipolar depressed inpatients, to treatment suggested by the trained ART (N = 21) and by the consensus of two senior psychiatrists (N = 33). The patients were allocated blindly and randomly to the two treatment groups. The BPRS (for the schizophrenic patients) or the HDRS (for the unipolar depressed patients) was completed weekly for 5 weeks. Results showed no difference between decisions regarding treatment by the ART network and by the experts. Length of hospital stay was also similar. All ART suggestions included supportive psychotherapy. High potency antipsychotics were suggested for 7 schizophrenic inpatients, clozapine for one and the addition of community therapy for another. Depressed patients got a variety of treatment suggestions. No contraindicated treatment was suggested by ART; however, two incomplete treatment suggestions were dropped from the study. In conclusion, in a prospective study ART was successful in learning treatment strategies and performed under supervision similar to experts.