Chronic Kidney Disease Detection Using Deep Learning Algorithm


  • Ganga R., Jayasheeli A., Pandiya Rajan G.


Chronic Kidney Disease (CKD) refers to damaged kidneys that do not filter your blood properly. As a kidney's primary function is to filter your blood of extra water and waste, CKD occurs when wastes accumulate in the body due to overflow of the kidneys. A large number of people with CKD are increasing, implying that effective measurements are needed to ensure early diagnosis of CKD. CKD is among the top causes of death worldwide, affecting nearly one by tenth of the world adult population.  Researchers use machine learning techniques to improve early detection of CKD in order to optimize prevention. The purpose of this project is to develop a Deep Neural Network model to assess whether the patient is affected by chronic kidney disease. Deep Neural Network improves accuracy by increasing the number of hidden layers in the model. It is evaluated on twenty four feature patient dataset containing RBC count, blood pressure, blood sugar, etc. Therefore, machine learning techniques can be extremely useful in the early detection of kidney disease. They assist experts and doctors in detecting kidney disease at an early stage so that kidney failure can be avoided.