Wycliffe Nzoli Nzomo

Explainable AI for Breast Cancer Diagnosis: Comparative Analysis of ML Models Using Random Forest Feature Selection and SHAP Interpretability

John Kamwele Mutinda, Tecla Mutave Kyalo, Joyce Akhalakwa Mukolwe, Jackson Ndoto Munyao, Millicent Auma Omondi, Wycliffe Nzoli Nzomo, Titus Mutua Kioko, David Chepkonga, Samuel Kipsang Kaptum, Erick Munala Sifuna & Amos Kipkorir Langat · Asian Journal of Research in Computer Science · 2025

Breast cancer diagnosis is critical for improving patient outcomes, yet traditional methods face limitations such as invasiveness and human error. This study presents an explainable AI framework for breast cancer classification using six ML models: LR, NB, KNN, RF, SVC, and DT. S...