Using Artificial Intelligence Methods For Diagnosis Of Gingivitis Diseases
Baydaa Khaleel, Mohammad S. Aziz
Abstract
Abstract Artificial Intelligence Techniques, and image processing are playing a major role in medical science. In this paper, several methods of artificial intelligence techniques were used to diagnose Gingivitis disease. The Bat swarm algorithm, the Self-Organizing Map(SOM) algorithm and the Fuzzy Self-Organizing Map (FSOM)network algorithm were used to diagnose Gingivitis disease. Also, was used the traditional algorithm, which is the Principal Component Analysis (PCA) algorithm, for Feature Extraction of Gingivitis disease images. We compute the diagnostic accuracy on this images dataset. Next, we compared the final results of these three methods used and applied to this data. In this paper the best of these methods is the BAT, because in testing state the BAT was obtained higher accuracy for diagnose of Gingivitis disease equal (97.942%).