A Comparative Study of Diagnosing Thyroid Diseases Using Classification Algorithm

A. Sivasakthivel, G. T. Shrivakshan


Data mining based applications are very useful and significant in healthcare and medical science. In health care, there are large volume of data, and this data has no structural value until converted into information and knowledge, which can help increase profits, control costs and maintain high quality of patient care. The classification is one of the most important applications of data mining technique. It is one of the most important decision making techniques in many real world problem. The main objective of this work is to analyze the several efforts made on the classification of thyroid data, the different classification techniques based on statistical techniques and soft computing techniques and their obtained results. In the field of healthcare the Data mining based classification plays an important roles.In the field of medical science Diagnosis of health conditions is a very important and challenging task. There are several types of diseases are diagnosis in medical science. Thyroid disease is one of serious diseases that is very major problem and affected the health of human being. Classification of Thyroid decease is one of the significant problems in medical science since it is directly related to health condition of human body; this type of disease can be cured by accurate identification and give correct treatment. This paper compare various classification algorithms such as J8, CART and Random Forest used for prediction on the diagnosis of thyroid. Several authors have worked in the field of thyroid diseases classification and give the proper classification accuracy with strong model.

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DOI: https://doi.org/10.23956/ijarcsse.v7i8.47


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