A Deep Neural Network for Early Detection and Prediction of Chronic Kidney Disease
University of Petroleum and Energy Studies · University of Dayton · +1 more institution
Abstract
Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep neural network and compare its performance to that of other contemporary machine learning techniques. In tests, the average…
Citation impact
- FWCI
- 57.98
- Percentile
- 100%
- References
- 54
Authors
3- VSVijendra SinghCorresponding
University of Petroleum and Energy Studies
- VKVijayan K. Asari
University of Dayton
- RRRajkumar Rajasekaran
Vellore Institute of Technology University
Topics & keywords
- Naive Bayes classifier
- Random forest
- Support vector machine
- Kidney disease
- Artificial intelligence
- Machine learning
- Logistic regression
- Computer science
- Good health and well-being