Abstract:
We describe a diagnostic support system for clinical psychiatry and its evaluation results. The system has two inter-related components: a rule-based reasoning part associated with uncertainty, and a deterministic part, that uses heuristics to perform categorical reasoning. The system includes the 30 groups of psychiatric diagnoses which are classified under the categories 290 to 319 of the DSM-III-R and the ICD-9. There are, in fact, 1508 rules relating 208 clinical findings with 257 diagnoses. The reasoning strategy is based on selecting and differentiating diagnostic categories in a hierarchical classification tree. The system is intended to be used for education of medical students, and to help non-specialist clinicians, residents in psychiatry, or experts with few years of experience in decision making. We tested the diagnostic performance of the system using case reports extracted from a specialized journal. In 52.8% of the cases, the correct diagnosis was ranked as the first hypothesis using only the rule-based part. In combination with the deterministic strategy, the correct diagnosis could be made for 73.6% of the analyzed cases.
Keywords:
Artificial Intelligence - Psychiatry - DSM-III-R - Diagnostic Reasoning - Expert Systems