Machine Learning Techniques to Thyroid Diagnosis and Treatment Prediction

Abstract

Abstract: The thyroid is a steroid hormone that is located in the front of the neck. Its main function is to produce the thyroid gland, that is necessary for our overall health. This is a probable failure can result in thyroid hormone production that is either insufficient or excessive. As a result of one or maybe more swellings growing inside the thyroid, it might become inflamed or enlarged. Some of these nodules may harbor cancerous tumors. Sodium levothyroxine, generally defined as LT4, is a synthesized thyroid hormone used to treat thyroid problems and diseases and is one of the most commonly used medications. Predictions about therapy can help endocrinologists do their jobs better and enhance the quality of life for their patients. Numerous research has been published to date which focuses on the prognosis of thyroid illnesses based on the development of people's hormonal markers. This study, on the other hand, tries to forecast the LT4 therapy trend for hypothyroidism patients. A specific dataset containing clinical records on patients treated at Naples' "AOU Federico II" hospital was created to achieve this purpose. Because each patient's whole medical history can be accessed at any moment, it was possible to forecast the duration of each patient's therapy based on the trend of hormonal attributes and other features analyze, in order to determine whether it should be raised or decreased. We used a variety of machine learning methods to conduct this research. In specifically, we looked at the results of ten classification techniques. The findings of the various methods are promising, specifically in the context of the Additional Classifier, which achieves an accuracy of 84 percent.