AI-Driven Prediction of Chronic Kidney Disease with Transparent Insights

Abstract

Chronic Kidney Disease (CKD) continues to be a driving force contributing to global illness and mortality, and early diagnosis is crucial in averting additional complications. Despite advancements in diagnostic tools, current methods often fall short in providing transparent and interpretable insights into the risk factors driving disease progression. A new approach is used in this work for CKD prediction by utilizing the power of Explainable Artificial Intelligence (XAI) with machine learning. The proposed model provides predictions alongside clear, interpretable explanations, empowering healthcare providers to make more informed, data-driven decisions using two features: hemo, sg. Through testing on a publicly available CKD dataset, we show that our model offers crucial interpretability, fostering greater trust and utility in clinical settings.