The education and practice of clinical medicine can benefit significantly from the use of computational assistants. The authors describe the development of a prototype system called SURGES (Strong/University of Rochester Gynecological Expert System) for representing medical knowledge and then applying this knowledge to suggest diagnostic procedures in medical gynecology. They focus on the representation technique of property inheritance, which facilitates the simple common sense reasoning required to enable execution of the more complex medical inferences. Such common sense can be viewed as a collection mundane inferences, which are the simple conclusions drawn from knowledge that an exclusive or (XOR) relation (i. e. , mutual exclusion) holds among a number of facts. The authors also discuss the use of a property hierarchy for this purpose and show how it simplifies knowledge representation in medical artificial intelligence (AIM) computer systems.