Decision making in acupuncture is a complex process, once there is a great variety of elements and circumstances to be considered during the treatment. The diagnosis, a knowledge-intensive task, is fundamental for the success of the treatment. Therefore, this study proposes a knowledge system based on the CommonKADS methodology aiming to support diagnosis tasks and to minimize the level of uncertainty in order to improve patient health conditions and welfare. The proposed model is validated through acne diagnosis prototype using Bayesian networks.
Knowledge engineering; CommonKADS methodology; Acupuncture; Ontology; Diagnosis; Knowledge systems
