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    A Machine Learning Based Early Diagnosis System for Mesothelioma Disease
    (2020) Senturk, Zehra Karapınar; Cekic, Nagihan
    Mesothelioma is pleura cancer that cause death in about one year after diagnosis. The disease causes pain andshortness of breath. Patients have a CT (Computed Tomography)-scan and lung x-ray traditionally, but the exactmethod is biopsy. There are also different biopsy methods for its diagnosis. Its prevalence is one or two in amillion around the world, but for Turkey it is disastrous. Five hundred people are diagnosed as mesothelioma everyyear in Turkey. This serious rate makes early diagnosis systems crucial for mesothelioma. In this paper, a machinelearning based early detection system has been proposed for this fatal disease. An open database is used for theexperiments and different methods have been applied to the problem of diagnosing mesothelioma disease.Accuracy and sensitivity performance metrics were used for the evaluation of the methods. The results show thediagnostic performance of different machine learning methods and present a successful early diagnosis system.