Paper Contents
Abstract
Chronic Kidney Disease (CKD) is a progressive condition characterized by the gradual loss of kidney function over time. It has become a major global health issue, affecting millions of individuals worldwide. Early detection of CKD is critical to prevent severe complications, including kidney failure and cardiovascular diseases. However, the asymptomatic nature of CKD, particularly in its early stages, poses significant challenges for timely diagnosis and treatment.In recent years, advancements in machine learning (ML) have revolutionized the healthcare industry, offering robust solutions for disease prediction and diagnosis. ML algorithms excel at analyzing complex datasets, identifying patterns, and making accurate predictions, even in cases where symptoms are minimal or absent. These capabilities make ML an ideal tool for addressing the challenges associated with CKD detection.
Copyright
Copyright © 2025 Mr. Narsimhulu Bommineni. This is an open access article distributed under the Creative Commons Attribution License.
