Thyroid Disease Detection using Machine Learning

Abstract

Thyroid detection is a critical task in medical diagnosis, necessitating the development of precise and efficient methods. This paper introduces a machine learning approach utilizing the Random Forest algorithm for thyroid presence detection. A dataset comprising thyroid images is employed to train the algorithm, and its performance is evaluated using multiple metrics. Our findings indicate that the Random Forest algorithm is a dependable and accurate method for detecting the presence of thyroid in individuals.