Chronic Kidney Disease Classification Using Entropy Based Butterfly Optimization and Improved Artificial Neural Network Algorithm: Preprocessing, Feature Selection, Clustering, and Disease Prediction

M. Lincy Jacquline ^1*, N. Sudha ¹

This study determined advanced AI techniques for accurate CKD diagnosis, enhancing medical decision-making through efficient data analysis methods.

Abstract

Background: Chronic diseases, which are the leading cause of death globally, account for most medical expenses. Early detection of chronic diseases is crucial for effective preventative medicine. However, the complex nature of these diseases makes accurate early diagnosis challenging. Artificial intelligence (AI) technology has shown promise in assisting clinicians by automating diagnostic processes through predictive models. Methods: This study proposes a classification framework for chronic kidney disease (CKD) using an Enhanced Butterfly Optimization and Improved Artificial Neural Network (EBO-IANN) algorithm. The framework includes preprocessing using the K-means clustering (KMC) algorithm, feature selection via the EBO algorithm, clustering with Weighted Fuzzy C-means (WFCM), and classification using IANN. Results: The proposed EBO-IANN algorithm was evaluated on the CKD dataset from the UCI repository. The framework demonstrated superior performance compared to existing methods, including Bayesian, Neural Networks (NN), Modified K-means Support Vector Machine (MKSVM), and Enhanced Adaptive Neuro-Fuzzy Inference System (EANFIS). The EBO-IANN achieved higher precision, recall, F-measure, and accuracy. Specifically, it showed a precision of 98.9% and 95.9% for the CKD and Hungarian datasets, respectively, with no misclassified features. Conclusion: The EBO-IANN algorithm effectively enhances CKD classification by optimizing feature selection and classification accuracy. This approach can significantly aid in the early detection and treatment of CKD, potentially improving patient outcomes and reducing healthcare costs.

Keywords: Chronic Kidney Disease (CKD), EBO-IANN Algorithm, Preprocessing, Feature Selection, Clustering, Disease Classification

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