In India, thyroid illness is a common condition that affects over a million people yearly, mostly women. The most prevalent thyroid diseases, hyperthyroidism and hypothyroidism, are brought on by the thyroid gland’s abnormal activity, and they may either raise or lower the body’s metabolism. The use of artificial intelligence in the healthcare sector is a result of the industry’s ongoing technological innovation and advancements. Algorithms based on machine learning can detect thyroid diseases asymmetrically, improving overall health. This research shows how several classification methods, such as Support Vector Machine, Random Forest, Decision Tree, Naïve Bayes, and Logistic Regression, can predict the existence of thyroid illness. The models were evaluated and compared to see which produced the greatest results.

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