Izdihar Al-muwaffaq and Zeki Bozkus, Kadir Has University, Turkey

Machine learning algorithms are used to diagnosis for many diseases after very important improvements of classification algorithms as well as having large data sets and high performing computational units. All of these increased the accuracy of these methods. The diagnosis of thyroid gland disorders is one of the application for important classification problem. This study majorly focuses on thyroid gland medical diseases caused by underactive or overactive thyroid glands. The dataset used for the study was taken from UCI repository. Classification of this thyroid disease dataset was a considerable task using decision tree algorithm. The overall prediction accuracy is 100% for training and in range between 98.7% and 99.8% for testing. In this study, we developed the Machine Learning tool for Thyroid Disease Diagnosis (MLTDD), an Intelligent thyroid gland disease prediction tool in Python, which can effectively help to make the right decision, has been designed using PyDev, which is python IDE for Eclipse.

Machine Learning, Thyroid diseases, CRT decision tree algorithm, PyDev, Python IDE.