A review on machine learning driven models for early diagnosis of chronic kidney diseases

Abstract

This study a provides a detailed review of research studies on machine-learning models that have been applied to classify chronic kidney diseases (CKD). Machine learning applications or models have become more popular for classification or diagnosis pf CKD since this is a major global health issue. This review examines a variety of studies which use diverse machine-learning algorithms, data sources and feature selection techniques to classify CKD. This review also highlights their contributions in terms of accuracy and other performance metrics. It sheds light on the potential of these models to revolutionize CKD diagnosis. This review aims at providing valuable insight for data scientists, researchers and clinicians who are interested in harnessing the power of machine-learning to advance CKD classifier strategies.