Prediction of CKDu using KDQOL score, Ankle Swelling and Risk Factor Analysis using Neural Networks

Abstract

Chronic Kidney disease (Chronic Kidney Disease (CKD)) is a type of kidney disease where gradual loss of kidney function occurs over a period of months to years. But, when CKD cannot identify a manner or causation of the disease or set of causes it is known as Chronic Kidney disease with unknown etiology (CKDu). There are several factors to be considered when analyzing the main causes for CKDu such as socio-economic, environmental, meteorological and health aspects in relation to the CKDu in Sri Lanka. In this research work, identification of CKDu has been done using the relationship of the Kidney Disease Quality of Life (KDQOL) score, ankle swelling with the serum creatinine level of blood and considering risk factors. This research has been done using three major branches of Artificial Intelligence namely neural networks, convolutional neural networks and machine learning. The relationship between the mentioned factors and CKDu has been identified. The sensitivity of 77.27% and a specificity of 89.28% have been marked for the detection of CKDu related to ankle swelling.