| dc.description.abstract | Kidney disease, also known as chronic kidney disease, is a public health problem around the world, and kidney failure is one of the top ten causes of death in the world, and early detection or prediction of the disease is very important for the health of patients, and this disease is growing increase. The purpose of this paper is to use machine learning techniques to predict kidney disease. Biological data collected from patients with kidney disease is used as the basis for a system for predicting kidney disease. We also hope that the presence of this system contributes to helping many patients, and such a system is considered as a decision support system used by medical professionals. This paper focuses on the use of patient databases on an Artificial Neural Network (ANN) in order to predict kidney disease, obtaining the accuracy possible by using a different number of nodes in the hidden layer in each trial. Also the best accurate results were 94% which was obtained when we used 54 nodes in the hidden layer. | en_US |
