Machine learning techniques for thyroid disease diagnosis - A review

Abstract

Background/Objective: Thyroid is an interminable and complex infection happened because of unseemly TSH (Thyroid Simulating Hormone) levels or might be brought on by the issues in thyroid organ itself. The most widely recognized reason for hypothyroidism is hashimoto's thyroid. It is an auto safe condition where the body makes antibodies that pulverize the thyroid organ. The system behind the flow of the event of the thyroid ailment is still not completely caught on. Methods/ Analysis: The neural network models which describe the aspects related non functionality of thyroid gland, its autoimmune condition and different aspects of thyroid disease have been explored. The consequences related to thyroid disease are growing rapidly and provides new insights into the biological mechanism involved and helps in the management of thyroid disease. Here, the contribution of different neural network modeling in identifying the thyroid dysfunctionality over the past two decades has been discussed. Results: Some parameter estimation methods, execution of the distinctive neural system models have been explored. Additionally, the utilization of the distinctive neural system models for distinguishing the dis functionalities of thyroid disease in the recent decades has been talked about.