Feature selection of Thyroid disease using Deep Learning: A Literature survey

Authors : Amir MEHRNO, Recai OKTAŞ, Mehmet Serhat ODABAS

Pages : 109-114

Doi:10.34248/bsengineering.695904

View : 16 | Download : 9

Publication Date : 2020-07-01

Article Type : Review Paper

Abstract :The thyroid hormone, which is secreted by the thyroid gland, helps regulate the body`s metabolism. Thyroid disorders can range from a small, harmless goiter that does not need to be treated for life-threatening cancer. The most common thyroid problems include abnormal production of thyroid hormones. Overproduction of the thyroid leads to the thyroid and inadequate hormone production leads to hypothyroidism. Although the effects can be unpleasant or uncomfortable, many thyroid problems can be managed well if they are timely diagnosed and treated correctly. In this paper, the diagnosis of thyroid disease is investigated using deep learning based on the imperialist competitive algorithm feature selection method.
Keywords : Thyroid disorders, Diagnosis, Deep Learning, feature selection method, imperialist competitive algorithm