Expert system for offline clinical guidelines and treatment

Offline clinical guidelines are typically designed to integrate a clinical knowledge base, patient data and an inference engine to generate case specific advice. In this regard, offline clinical guidelines are still popular among the healthcare professionals for updating and support of clinical guidelines. Although their current format and development process have several limitations, these could be improved with artificial intelligence approaches such as expert systems/decision support systems. This paper first, presents up to date critical review of existing clinical expert systems namely AAPHelpm, MYCIN, EMYCIN, PIP, GLIF and PROforma. Additionally, an analysis is performed to evaluate all these fundamental clinical expert systems. Finally, this paper presents the proposed research and development of a clinical expert system to help healthcare professionals for treatment.