The study of chronic kidney disease of human body is now a significant topic of interest in the domain of biosciences because of the emerging cases of the disease. One of the most dangerous illnesses in the modern world is chronic kidney disease, for which an accurate diagnosis method needs to be developed to identify and stop the disease at an early stage. A condition known as chronic kidney disease causes a person's kidneys to malfunction and eventually become damaged. This leads to the condition where the kidney is unable to filter the blood and remove the waste as they do. Now-a-days machine learning algorithms have become a major tool in which the disease gets diagnosed based on the certain values like blood pressure, urine value and many such things. This leads to the early detection of the disease so that the patient can consult his required doctor and with the help of which his disease could be cured. The application and the study of the applied algorithm will help us to detect the disease will be explored in this study. These algorithms' outputs have a higher degree of accuracy, sensitivity, and specificity and can be used to predict the presence of chronic kidney disease in the necessary human being. The findings will demonstrate how technology can aid in the better management of chronic kidney disease and how this can enhance decision support systems for healthcare in general.
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Shukla et al. (2024) studied this question.
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