Applications of Machine learning (ML) in health informatics have gained increasing
attention. The timely diagnosis of kidney disease and the subsequent immediate response …

Background and objective Aim of nephrologists is to delay the outcome and reduce the
number of patients undergoing renal failure (RF) by applying prevention protocols and …

In recent days, the gigantic generation of medical data from smart healthcare applications
requires the development of big data classification methodologies. Medical data …

Artificial intelligence (AI) is expanding its roots in medical diagnostics. Various acute and
chronic diseases can be identified accurately at the initial level by using AI methods to …

Chronic kidney disease (CKD) is a global health burden that affects approximately 10% of
the adult population in the world. It is also recognized as the top 20 causes of death …

The high incidence and prevalence of chronic kidney disease (CKD), often caused by late
diagnoses, is a critical public health problem, especially in developing countries such as …

Chronic kidney disease (CKD), also known as chronic renal disease, which is progressive
loss in kidney function over a period of months or years. It is defined by the presence of …

This paper implies an investigative approach to study the performance of different boosting
algorithms in predicting chronic kidney disease (CKD) more accurately. In recent years, CKD …

Chronic kidney disease (CKD) is a gradual decline in renal function that can lead to kidney
damage or failure. As the disease progresses, it becomes harder to diagnose. Using routine …

Individuals with chronic kidney disease (CKD) are often not aware that the medical tests they
take for other purposes may contain useful information about CKD, and that this information …