MESICAR is a second generation expert system which contains very general disease descriptions about rheumatological disorders in the primary medical care field. With the help of a detailed hierarchical description of the human anatomy the system is able to support diagnostic decisions. The current paper describes how Machine Learning techniques are used to automatically build more specific disease descriptions for common, frequently occurring cases. Integrating learned concepts into the hierarchy of disease descriptions supports efficient and fast reasoning on common cases in addition to the general diagnostic support for rheumatological problems of anatomical structures.