Title :
Diagnosis of thyroid disease using artificial neural network methods
Author :
Ozyilmaz, Lale ; Yildirim, Tulay
Author_Institution :
Electron. & Commun. Eng. Dept, Yildiz Tech. Univ., Istanbul, Turkey
Abstract :
Proper interpretation of the thyroid gland functional data is an important issue on the diagnosis of thyroid disease. The primary role of the thyroid gland is to help regulation of the body´s metabolism. Thyroid hormone produced by the thyroid gland provides this. Production of too little thyroid hormone (hypo-thyroidism) or production of too much thyroid hormone (hyper-thyroidism) definites the type of thyroid disease. In this work, various neural network methods have been used to help diagnosis of thyroid disease.
Keywords :
feedforward neural nets; medical diagnostic computing; diagnosis; neural network; thyroid disease; thyroid gland functional data; Artificial neural networks; Biochemistry; Diseases; Glands; Manufacturing; Medical diagnostic imaging; Neural networks; Production; Proteins; Temperature;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1199031