International Journal of Scientific Research and Engineering Development

Thyroid disorders affect millions of people and can cause several health problems including fatigue, weight changes, weakness, mood changes, and irregular heart rate, as well as difficulties in maintaining normal body functions. Since symptoms can develop gradually, healthcare professionals may require laboratory investigations and clinical evaluation to identify thyroid abnormalities accurately. This paper introduces the Automated Biological Diagnosis System for Thyroid Disorder, an AI-based diagnosis-support system that can provide early preliminary screening and assist in identifying possible thyroid conditions. The proposed architecture is built around patient information, selected symptoms, and important biological parameters such as TSH, T3, and T4, allowing continuous analysis of relevant health information. In addition, the system provides a user-friendly interface where patients can select symptoms, enter laboratory values, and receive a preliminary prediction based on a trained machine learning model. The system can maintain patient records and provide automated prediction results when required. The proposed architecture is practical and deployable as a clinical decision-support application for preliminary thyroid disorder screening. Index Terms - Thyroid Disorder, AI Diagnosis, Machine Learning, TSH, T3, T4, Symptom Analysis, Healthcare, Medical Prediction, Automated Diagnosis.

Prajwal G K, Mrs. Bhavya B V, Veeresh, Sambram S, Sai Mohan S M, "Automated Biological Diagnosis System for Thyroid Disorder" International Journal of Scientific Research and Engineering Development, V9(4): Page(1267-1273) July-August 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.