Thyroid Cancer Detection

Abstract

Abstract: In the recent world of Digital and Technology,the level of disease rate also increases with time. According to the World Health Organization, the second most common endocrine disorder in the world is relatedto thyroid gland diseases which is next to diabetes. Hypothyroidism or hyperthyroidism is a major issue in India which rises due to non-functional thyroid hormones. This study proposes a machine learning framework to predict thyroid cancer based on our collected clinical dataset. The ten-fold cross-validation, bootstrap analysis, and permutation predictor importance were applied to estimate and interpret the model performance under uncertainty. The comparison between model prediction and expert assessment showsthe advantage of our framework over human judgment in predicting thyroid cancer. Our method is accurate, interpretable, and thus useable as additional evidence in the preoperative diagnosis of thyroid cancer.This diagnosis of Thyroid Cancer is very monotonous and tough tasks at early steps with accuracy. The Accuracy prediction can be done through various Machine Learning Algorithms.