Diagnosis of Thyroid Gland Disorder using Machine Learning Techniques
Abstract
Thyroid is an endocrine gland which secretes the thyroid hormones.An Imbalance in the production of thyroid hormones may lead to Thyroid Gland disorder. Thyroid is one of the most common diseases found in human beings. It is a chronic disease which can give rise to other diseases. Machine learning is widely used in health care for detection and diagnosis of many diseases, which can help human beings to fight against diseases and it is important for better treatment. The data set used for thyroid prediction are taken from the UCI repository. Classification algorithms like SVM, Decision tree,KNN, Random forest, XG boost,Logistic regression are the algorithms used to prognosticate Thyroid. The aim of this work is to propose a quicker and more efficient technique for diagnosing the problem, leading to timely treatment of the patient.
Keywords: Decision tree, KNN, Logistic Regression, Machine Learning, Random forest, SVM, XGBoost.