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- W2186080204 abstract "Data Mining usage in Health Sector increased much in this decade because of the need for efficient treatment. From cost-cutting in medical expenses to acting as a Decision Support System for patient diagnosis, Data Mining nowadays is a strong companion in Health Sector. The dataset used in this thesis belongs to Dr. Nurhan Seyahi. Dr. Nurhan Seyahi and his colleagues made a research about Coronary Artery Calcification in 178 patients having renal transplantation recently. They used conventional statistical methods in their research. By using the power of data mining, this thesis shows the importance of feature selection and discretization used with classification methods for acting as a decision support system in patient diagnosis for CAC Dataset. Just by looking at seven important attributes, which are; age, time of transplantation, diabetes mellitus, phosphor, rose angina test, donor type and patient history, doctors can decide whether the patient has coronary artery calcification or not with approximately 70% accuracy. After the discretization process this accuracy approximately increases to 75% in some algorithms. Thus becoming a strong decision support system for doctors working in this area." @default.
- W2186080204 created "2016-06-24" @default.
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- W2186080204 date "2013-01-01" @default.
- W2186080204 modified "2023-09-27" @default.
- W2186080204 title "Importance of Data Preprocessing For Improving Classification Performance on CAC Data Set" @default.
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