Survey on Thyroid Diagnosis using Data Mining Techniques

Abstract: Recently, thyroid diseases are more and more spread worldwide. India, for example, one of eight women suffers from hypothyroidism, hyperthyroidism or thyroid cancer. Factors that affect the thyroid function are: stress, infection, trauma, toxins, low-calorie diet, certain medication etc. It is very important to prevent such diseases rather than cure them, because the majority of treatments consist in long term medication or in chirurgical intervention. The current study refers to thyroid disease classification in two of the most common thyroid dysfunctions (hyperthyroidism and hypothyroidism) among the population. The authors analyzed and compared four classification models: Naive Bayes, Decision Tree, Multilayer Perceptron and Radial Basis Function Network. The results indicate a significant accuracy for all the classification models mentioned above, the best classification rate being that of the Decision Tree model. Keywords: Data Mining, Classification Model, Thyroid Diseases, Neural Network, Decision Tree, Na�ve Bayes, Chi Square.