Hyperparameter-Tuned Logistic Regression for Early-Stage Breast Cancer Prediction using Explainable AI

• Design of HTLR model using optimized logistic regression applied to early stage breast cancer prediction.

• Integration of SHAP for model interpretability, supporting clinicians in extracting key features affecting malignant and benign predictions.

• Comparative analysis with baseline state-of-the-art models and existing systems, demonstrating that the proposed HTLR achieved 99.12% accuracy while providing transparent and clinically meaningful explanations.