Prominent Features based Chronic Kidney Disease Prediction Model using Machine Learning

Chronic Kidney disease is a significant public health concern across the world, with rising incidence and prevalence, as well as negative effects such as renal failure, cardiovascular disease, and early mortality. A condition where the kidney reaches advanced state of loss of function. Unfortunately, there is no treatment for this condition; but, by detecting it early, it is possible to halt its growth and mitigate the harm. As a result, recognizing such sickness at an early stage is now a major concern. If risk factor for chronic kidney disease can be predicted at early stage it can be cured on time and appropriate action can be taken. To overcome this challenge Machine Learning plays an important role along with mining tools. This research study has proposed a novel feature selection method for selecting the prominent features to improve the performance of predictive model. As there is scope of improvement in performance with original instances so by selecting prominent features the performance of predictive is found to be quite satisfactory.