Abstract

Data mining Techniques play a vital role in healthcare organizations such as for decision making, diagnosing disease and giving better treatment to the patients. Thyroid gland plays a major role in maintaining the metabolism of human body. By using data mining in health care industry can provide health systems a way to systematically use the medical data. Thyroid diseases are most common today. Early changes in the thyroid gland will not affect the proper working of the gland. By the early identification of thyroid disorders, better treatment can be provided in the early stage thus can avoid thyroid replacement therapy and thyroid removal up to an extent. This paper proposes a method for the diagnosis of thyroid disease. Correlation analysis and Feature extraction using Genetic Algorithm is performed in data preprocessing stage. Support Vector Machine is used for classification. To optimize SVM parameters Grid Search parameter tuning method is used. KNN imputation method is used for approximating the missing values in the user input.

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