When the obtained results were examined, it has been seen that Artificial Neural Network (ANN) had %99.0740 correct classification ratio.
📌 3 Key Takeaways
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Objective & Hypothesis:Mesothelioma, which is a disease of the pleura and peritoneum, is an asbestos-related environmental disease in undeveloped countries.
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Key Findings & Data:In this study, 9 different classification algorithms of data mining were applied to the Mesethelioma data set obtained from real patients in Dicle University, Faculty of Medicine and loaded into UCI Machine Learning Repository, and the results were compared.
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Conclusion & Impact:When the obtained results were examined, it has been seen that Artificial Neural Network (ANN) had %99.0740 correct classification ratio.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Özet
Mesothelioma, which is a disease of the pleura and peritoneum, is an asbestos-related environmental disease in undeveloped countries. Although the incidence of this disease is lower than that of lung cancer, the reaction it creates in society is very high. In this study, 9 different classification algorithms of data mining were applied to the Mesethelioma data set obtained from real patients in Dicle University, Faculty of Medicine and loaded into UCI Machine Learning Repository, and the results were compared. When the obtained results were examined, it has been seen that Artificial Neural Network (ANN) had %99.0740 correct classification ratio.
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Cite This Article
TUTUNCU, K., ÇATALTAŞ, Ö. (2017). Diagnosis of Mesothelioma Disease Using Different Classification Techniques. International Journal of Intelligent Systems and Applications in Engineering, Cilt: 5 - Sayı: 0, 7–11. https://ajindex.com/articles/193335
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