Abstract: Thyroid disorders affect metabolism, mood, and health, often going undetected until severe. This project develops a machine learning-based system for early detection and classification of thyroid conditions like hypothyroidism and hyperthyroidism using health data from CSV datasets. It also predicts recurrence risk and provides personalized health recommendations, including diet, meditation, and medication advice. Powered by Python, Flask, and SQLite, with XG Boost and Cat Boost algorithms, the system ensures high accuracy. By integrating robust preprocessing, exploratory analysis, and evaluation, it empowers users with actionable insights for proactive thyroid disorder management.
Keywords: Thyroid Disorder, Thyroid Classification, Thyroid Recurrence, Hypothyroidism, Hyperthyroidism, Personalized Advice, Health Recommendations.
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DOI:
10.17148/IJARCCE.2025.14106
