Hybrid Framework for Chronic Kidney Disease Prediction: Integrating Adaptive Neuro-Fuzzy Inference System and LIME

Chronic Kidney Disease (CKD) affects millions of people worldwide, making early detection critical for effective management and treatment. This paper presents a novel approach for CKD prediction using a hybrid model that combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) with Local Interpretable Model-agnostic Explanations (LIME). The ANFIS framework integrates fuzzy logic for managing uncertainty, while LIME enhances model interpretability by explaining individual predictions. Experimental results demonstrate that this hybrid model achieves competitive accuracy and provides actionable insights, making it a valuable tool for healthcare professionals.