Authors : S Kumar Reddy Mallidi; G.Dinesh Karthik; M.Lok Satish; D.N S Venkatesh; G.K Sai sashank; R.N V Subrahmanyam

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/5x9nx3dy

Scribd : https://tinyurl.com/bdhr3tuy

DOI : https://doi.org/10.38124/ijisrt/25apr664

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Thyroid disorders, particularly hypothyroidism, are a significant global health concern that requires timely diagnosis and effective management. This project introduces a smart, innovative system for the detection and classification of thyroid disorders using hybrid machine-learning techniques. By analyzing key thyroid function indicators, such as TSH blood test results, the system accurately classifies patients as having primary, secondary, or no thyroid disorder, assisting healthcare professionals in early detection and treatment planning. Integrated into a user-friendly platform, the system features a chatbot that provides instant answers about thyroid health, offering guidance on symptoms, causes, and treatment options. By combining accurate classification, an interactive chatbot, and educational resources, this project offers a comprehensive approach to improving thyroid health management.

Keywords : Hypothyroid, Flask, Chatbot, Random Forest, KNN, K-Means.

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