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

The latest advances in eHealth and mHealth have propitiated the rapidly creation and
expansion of mobile applications for health care. One of these types of applications are the …

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD).
Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers …

Abstract As Chronic Kidney Disease progresses slowly, early detection and effective
treatment are the only cure to reduce the mortality rate. Machine learning techniques are …

Chronic kidney disease (CKD) is one of the most critical health problems due to its
increasing prevalence. In this paper, we aim to test the ability of machine learning algorithms …

The high morbidity rate associated with kidney stone disease, which is a silent killer, is one
of the main concerns in healthcare systems all over the world. Advanced data mining …

We have developed an artificial neural network prediction model for end-stage kidney
disease (ESKD) in patients with primary immunoglobulin A nephropathy (IgAN) using a …

Data mining is a non-trivial process of categorizing valid, novel, potentially useful and
ultimately understandable patterns in data. In terms, it accurately state as the extraction of …

Data Mining is used to extract the valuable information from raw data. The task of data
mining is to utilize the historical data to discover hidden patterns that helpful for future …

Imbalanced data is an important problem for medical data analysis. Medical datasets are
often not balanced in their class labels. The traditional classifiers can be seriously affected …