A Statistical Review on Machine Learning Based Medical Diagnostic Systems for Chronic Kidney Disease
Arvind Sharma, Dalwinder Singh
Abstract
The decision making is a very challenging and complex process while doing the diagnosis of any specific illness. Huge ambiguities and problems are faced in the process of diagnosing by using the human visual system, which leads to conclusions that are inappropriate and unsuitable for a chronic kidney disease diagnosis. The employment of artificial intelligence approaches can overcome these limitations as these techniques help an expert doctor to offer precise and high-quality care to the patent suffering from CKD. Numerous publications enlighten the usage of machine learning methodologies along with its benefits, and the number of publications is elevated day by day. The primary focus of this study is to statistically review the various proposed and developed medical diagnostic systems for the diagnosis of chronic kidney disease using machine learning algorithms. The conducted review is categorized based on some criteria such as the objective of research work, its publication year, research gap and results obtained by researchers.