Early Prediction of Chronic Kidney Disease: A Comprehensive Survey

Jayaprabha, M. S. and Vishwa Priya, V. (2024) Early Prediction of Chronic Kidney Disease: A Comprehensive Survey. In: 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), Lalitpur, Nepal.

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Abstract

Chronic Kidney Disease (CKD) is a global health crisis, affecting millions worldwide and imposing substantial health and economic burdens. It provides a comprehensive overview of CKD, emphasizing its status as a pressing global health challenge. The significance of CKD is underscored by its increasing prevalence, economic impact, and high mortality rates, making it a silent but critical public health concern. Early Prediction and diagnosis of CKD are of paramount importance to mitigate the disease's impact. Detecting CKD at an early stage enables timely interventions, reducing complications, offering a wider range of treatment choices, and optimizing resource allocation within healthcare systems. Furthermore, we explore common symptoms of kidney disease, illustrating the severity and varied nature of these symptoms and highlighting the importance of early detection. The study delves into traditional diagnostic methods for CKD, their limitations, and the concept of early Prediction as a solution. We also discuss the significance of biomarkers, encompassing a range of measurable entities that provide crucial insights into CKD. These biomarkers, along with the integration of machine learning and data analytics, hold promise in improving risk assessment and early Prediction. The study details the machine learning algorithms applied to CKD Prediction, showcasing their potential to revolutionize the field. However, this promising approach faces several challenges, including data availability and quality, model interpretability, ethical considerations, model generalization, integration into clinical practice, and cost/resource allocation. Addressing these challenges is crucial to realizing the full potential of early CKD Prediction and enhancing patient outcomes. In this ongoing battle against CKD, the synergistic efforts of clinicians, researchers, and data scientists offer hope for improved patient care and reduced societal burdens. Early CKD Prediction, supported by these critical components, is poised to make a substantial difference in public health and the global fight against this pervasive disease.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science > Software Engineering
Divisions: Computer Science
Depositing User: Mr IR Admin
Date Deposited: 08 Oct 2024 09:32
Last Modified: 08 Oct 2024 09:32
URI: https://ir.vistas.ac.in/id/eprint/9471

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