A Machine Learning Approach to Thyroid Carcinoma Prediction

Abstract

A malignant tumor cell, such as a disorder, forms in the thyroid gland tissue, eventually leading to thyroid cancer. When malignant cancerous cells alter structure or change, thyroid cancer emerges. Mutated cells begin to develop in thyroid and eventually form a tumor if there are enough of cells. Thyroid cancer is one of the most curable forms of cancer if diagnosed early. The goal of this research is to use machine learning algorithms to analyse and forecast thyroid carcinoma based on the year, gender, and age group. The proposed research is a descriptive cross-sectional study that uses evidence in the form of data from the World Bank for Cancer on thyroid carcinoma incidence. The purpose of this research is to understand the global effects of thyroid cancer by gender and age. In the future, this paper will use a machine learning algorithm to predict accuracy on a minimal number of specific thyroid carcinoma attributes.