As mentioned before, there are many growing medical informational resources including textual information, audio and visual materials, clinical data and even physical processes that they should be represented. A good starting point for thinking about the representation of medical knowledge is the data required in solving medical problems (e.g. diagnosis); therefore it requires considering many relationships of obligatory or facultative proving or excluding symptoms for diagnosis and the corresponding therapies, as same as, expressing these relations in the form of logical networks in favor of inference. In addition to the above features, any successful representation of medical knowledge must contain certain basic features such as:

1. representation of vagueness and uncertainty in medicine
2. conformance with known clinical standards ( e.g. ICD-10, SNOMED, etc)
3. integration of patient data and medical knowledge, and,
4. (optionally) network capabilities to enable location independent consultations and knowledge acquisition

Representation of medical knowledge was one of the first efforts of the medical informaticians dating back to the late 1950’s research of Ledley and Lusted. Since then, it has been introduced several methods to represent medical knowledge. As an early experience in 1976, Alonzo Perez-Ojeda presented medical knowledge as a network of relationships that exist between symptoms and diagnoses linked together by logical relations. The basic conception of his master thesis, “Medical Knowledge Network, a Database for Computer Aided Diagnosis”, was the representation of medical knowledge using an associative model of the human memory. Perez-Ojeda designed a prototype system to be used in searching for an adequate strategy to simulate an approximate reasoning model in medical decision making. In addition to Perez-Ojeda’s approach, further models such as logical and causal models had proposed to represent medical knowledge; however none of them was in general use and commonly accepted. Among the most successful medical knowledge representation models, a more far reaching concept of modeling relationships between symptoms and diseases has been introduced by Elie Sanchez in his doctoral thesis. Sanchez planned to investigate medical aspects of fuzzy relations at some future time and in 1979 he introduced the relationship between symptoms and diagnoses by the concept of medical knowledge: “In a given pathology, let  and  be the set of symptoms and diagnoses, respectively, and  and  be the fuzzy power sets of  and . What we call medical knowledge is then the relationship between symptoms and diagnoses expressed by a fuzzy relation ”.