A FAST INTELLIGENT DIAGNOSIS SYSTEM FOR THYROID DISEASES BASED ON EXTREME LEARNING MACHINE

Abstract

With iodine taken from outside, the thyroid gland is an organ that secretes hormones called thyroxin. All metabolic functions of human beings are controlled by these hormones. An overactive thyroid gland which is producing an excessive amount of these hormones causes hyperthyroidism, while an underactive thyroid gland that is not producing enough of these hormones causes hypothyroidism. The diagnosis of thyroid gland disorders by assessing the data of thyroid in clinical applications comes out as an important classification problem. In this study, Extreme Learning Machine (ELM) was applied to the thyroid data set taken from UCI machine learning repository. The ELM is single hidden layer feed-forward artificial neural network model which can be learnt fast. It was seen that the ELM, for the data set, has the upper hand in terms of both classification accuracy and speed when compared to other machine learning methods. The classification accuracy obtained through the ELM is 96.79% for 70-30% training-test partition.