Smart Thyroid Diagnosis: A Machine Learning Based Interactive System

Thyroid disease is an important part of diagnosis and prognostication is a strenuous problem in initiating fact-finding research. One of the most vital organs in our body is the thyroid. The thyroid glands release of hormones controls metabolism. Hyperthyroidism and hypothyroidism are two disorders of the endocrine gland which secretes thyroid hormone to regulate the body's metabolic rate. A data cleaning process was used to obtain sufficient raw data to analyze to indicate a patient's susceptibility to thyroid conditions. The significance of machine learning is crucial. In the disease prediction process, and this article discusses the examination and categorization of thyroid illness models using Information gathered from the UCI Machine Learning Repository file. It is important to guarantee a strong base that can be combined and used as a hybrid model to difficult learning tasks such as diagnosis and prediction. In this piece, we'll also go over a lot of research and thyroid protection tests. To forecast patients' risk of thyroid illness, machine learning algorithms, K-NN, decision trees, and support vector machines are used.