Thyro Dectect: A Machine Learning Approach for Thyroid Disease Prediction

Abstract

According to the World Health Organization (WHO), approximately 300 million peoplesuffer from thyroid
related conditions, with women being more prone to than men. Thyroid disorders, encompassing conditions
like hyperthyroidism, hypothyroidism and thyroid nodule affect millions of people globally, with a
significant impact on their health and well- being. The proposed system aims to revolutionize thyroid
disorder prediction by leveraging machine learning algorithms. It utilizes a diverse dataset comprising
patient demographics, medical history, and thyroid-related parameters, training models to classify
individuals into four categories: Hypothyroidism, hyperthyroidism, negative, and sick. The objectives of the
proposed system include improved enhance diagnostic accuracy, early detection, offer personalized
predictions, and reduced healthcare cost.