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Objective: Malignant pleural mesothelioma is a highly\udaggressive tumor of the serous membranes, which in\udhumans results from exposure to asbestos and asbestiform\udfibers. The incidence of malignant mesothelioma\udis extremely high in some Turkish villages where there is\uda low-level environmental exposure to erionite, a fibrous\udzeolite. Therefore epidemiological studies are difficult to\udperform in Turkey.\udMethods: In this paper, a study on malignant pleural\udmesothelioma disease diagnosis was realized by using\udartificial immune system. Also, the artificial immune system\udresult was compared with the result of the multi-layer\udneural network focusing on malignant pleural mesothelioma\uddisease diagnosis and using same database. The\udmalignant pleural mesothelioma disease dataset were\udprepared from a faculty of medicine’s database using patient’s\udhospital reports.\udResults: 97.74% accuracy performance is obtained by\udartificial immune system. The accuracy results of artificial\udimmune system algorithm are much better than the accuracy\udresults of multi-layer neural network algorithm.\udConclusion: This system is capable of conducting the\udclassification process with a good performance to help\udthe expert while deciding the healthy and patient subjects.\udSo, this structure can be helpful as learning based decision\udsupport system for contributing to the doctors in their\uddiagnosis decisions

Health Status of Disabled Children and Youth Receiving Public Home Care Services Between 2010 and 2015 in Diyarbakir, Turkey