A case-based learning approach to grouping cases with multiple malformations.

A case-based classification system can provide assistance to specialists in dysmorphology. This article describes a case-based model designed to assist in identification and retrospective analysis of rare types of syndromes that have proved difficult to diagnose. The primary task of diagnosis is complemented by a learning, or grouping, task. Using data sets of diagnosed cases in related categories of syndromes, we demonstrate how a case-based learning algorithm can extend the retrieval and indexing mechanisms of standard databases to provide a focus for analysis of syndrome classifications.