A Medical Probabilistic Advisory System (MPAS) Based on Independent Artificial Intelligent Techniques to Support Decision Making

In this paper, an intelligent advisory system is used to make the decision depend on extracting the features of events by using artificial intelligence techniques. The proposed system was applied in the training in medical institutions in the field of physical therapy. X-ray images and their corresponding reports are used as events. For X-ray images, the Co-occurrence matrix is used to extract the features and Evidential K-Nearest Neighboring Rule has used to features classification then stored in the database. Whereas, the hidden Markov model is used to recognize the handwritten reports after their processing. The probability theory is used to solve the feature s overlapping problem that makes it easier to knowledge base formation by experts. The proposed system has been applied to different and several pathological patients of bone fractures and jaw and dental injuries. Comparing the results with the experts has shown the high accuracy that characterizes the proposed system