A Medical Probabilistic Advisory System Based on Independent Artificial Intelligent Techniques to Support Decision-Making

Document Type : Original Article

Author

7 Mahmoud Hekal St.

Abstract

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. 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 was characterized by high accuracy in the detecting of physical therapy reports after surgical cases or fractures, jaw and teeth injuries. Then the results stored in databases will be displayed on the expert that helped in the formation of the knowledge base. The results which were extracted from the proposed system are showed that it's convincing where, many of the patient's cases are applied and extract reports of treatment steps, which matched with the experts in the field.

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