Prediction of Thyroid Disease using Deep Learning Techniques

All over the world, people are affected by a variety of thyroid conditions. The thyroid gland is susceptible to many diseases, including thyroid cancer, hyperthyroidism, and hypothyroidism. Patients with thyroid disease may experience severe symptoms. To quickly diagnose thyroid diseases, effective categorization and machine learning are indeed very helpful. The patient's prompt treatment will be impacted by this classification. In this study, different machine learning as well as deep learning methods, including dense neural networks, have been applied to the data to produce a comparison analysis that would aid the researchers in improving their ability to predict the disease to use the dataset's specifications. The results of this study show how data mining and machine learning techniques can advance the medical field. This study will support the use of this by its doctors as such an additional system when following the established protocol. The dataset's accuracy and loss have been assessed. On training data and test data, dense neural networks were 99.45% and 99.15% accurate, respectively.