Deep Learning-Based Thyroid Disease Prediction with Fairness-Aware Evaluation: A Comparative Study Against Classical Machine Learning Approaches
Thyroid disease prediction using machine learning has been extensively studied, with existing literature dominated by classical algorithms such as Random Forest and XGBoost, often achieving accuracies exceeding 98% through careful imbalance handling and feature selection. However, two gaps remain: deep learning archite...