A Neural Expert System Based Dental Trauma Diagnosis Application
Senirkentli, Guler Burcu
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Dental traumas are frequently observed challenging medical situations that the dentists need to handle. This requires a quickly made correct diagnosis and treatment to prevent further complications. Follow up procedures also need to be properly planned for the treatment to be completed successfully. The main goal of this study is to develop a system that facilitates the diagnosis and treatment process for the general dentists and dental students by providing an easy method of accessing a standard guideline in dental traumatology. This system has a big advantage from another expert systems. By using neural network this system can create its own rule with examining previous diagnoses. Thus, the system can find new correlations never known before between symptoms. New correlations may provide faster and easier diagnosis. In this study, it was aimed to find new correlations by using multilayer perceptron algorithm in Weka framework. Although lack of scientific data, the system has showed us the capability of learning.