Treatment of thyroid disease through machine learning predictive model

Abstract

The thyroid seems to be an part of the endocrine system that is placed toward the front of neck and produces thyroxine, which are essential for our overall health. If it fails, thyroid hormone production will either be insufficient or excessive. Machine learning techniques and data mining are critical in processing large amounts of data, particularly in the health care system, where there has been a massive amount of information and data need to be managed. In our research on thyroid disease, we used machine learning approaches. In our study, we used statistics from patients, a few of which has hyperactive thyroid glands moreover those have hypothyroidisms; therefore, overall algorithms were used. These study aims to divide this disease in few categories like as hypothyroidism, regular and hyperthyroidism. Support vector machine include KNN, naive-bayes, logistic regressions, decision tree, random forest, discriminant function analysis, and multilayer perceptron (MLP). To the thyroid diseases classification.