Machine Learning Model for Accurate Prediction of Thyroid Disease

Thyroid disorder diagnosis and prognosis is an important concern in contemporary medicine. Thyroid hormones are essential for a healthy metabolic rate and are released by the thyroid gland. Either an excess of or a shortage in these hormones may interfere with the body's ability to regulate its metabolism. Forecasting disorders and researching thyroid disease classification models utilizing hospital information depend significantly on machine learning. In order to manage dynamic learning activities in medical diagnosis and prediction, a large knowledge base as a hybrid model is necessary. Using extremely basic machine learning approaches, thyroid disorders may be recognized and avoided. Using a support vector machine (SVM) model, our system should deliver home remedies, warnings, and medications to patients who are at risk for developing thyroid disease