[PDF][PDF] Machine learning-based prediction system for chronic kidney disease using associative classification technique

Z Wang, JW Chung, X Jiang, Y Cui… - International Journal of …, 2018 - academia.edu
Technological development, including machine learning, has a huge impact on health
through an effective analysis of various chronic diseases for more accurate diagnosis and …

[HTML][HTML] Chi2-MI: A hybrid feature selection based machine learning approach in diagnosis of chronic kidney disease

SK Dey, KMM Uddin, HMH Babu, MM Rahman… - Intelligent Systems with …, 2022 - Elsevier
Early detection and characterization are considered crucial in treating and controlling the
chronic renal disease. Because of the rising number of patients, the high risk of progression …

Prediction for chronic kidney disease by categorical and non_categorical attributes using different machine learning algorithms

S Pal - Multimedia Tools and Applications, 2023 - Springer
Chronic kidney disease (CKD) is a common disease as it is difficult to diagnose early due to
its lack of symptoms. The main goal is to first diagnose kidney failure, which is a requirement …

Diagnosis of chronic kidney disease using effective classification algorithms and recursive feature elimination techniques

EM Senan, MH Al-Adhaileh, FW Alsaade… - Journal of healthcare …, 2021 - Wiley Online Library
Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects
approximately 10% of the world adult population. CKD is a disorder that disrupts normal …

Efficient data preprocessing with ensemble machine learning technique for the early detection of chronic kidney disease

VK Venkatesan, MT Ramakrishna, I Izonin… - Applied Sciences, 2023 - mdpi.com
It is a serious global health concern that chronic kidney disease (CKD) kills millions of
people each year as a result of poor lifestyle choices and inherited factors. Effective …

Prediction of chronic kidney disease and its progression by artificial intelligence algorithms

FP Schena, VW Anelli, DI Abbrescia, T Di Noia - Journal of Nephrology, 2022 - Springer
Background and objective Aim of nephrologists is to delay the outcome and reduce the
number of patients undergoing renal failure (RF) by applying prevention protocols and …

A novel approach to predict chronic kidney disease using machine learning algorithms

B Gudeti, S Mishra, S Malik… - 2020 4th …, 2020 - ieeexplore.ieee.org
A staggering 63,538 cases have been registered according to India's health statistics on
Chronic Kidney Disease (CKD). The average age of nephropathy for humans lies between …

Comparative study of classifier for chronic kidney disease prediction using naive bayes, KNN and random forest

R Devika, SV Avilala… - 2019 3rd International …, 2019 - ieeexplore.ieee.org
Chronic kidney disease (CKD), is also known as chronic nephritic sickness. It defines
constrains which affects your kidneys and reduces your potential to stay healthy. There will …

An empirical evaluation of machine learning techniques for chronic kidney disease prophecy

B Khan, R Naseem, F Muhammad, G Abbas… - IEEE Access, 2020 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) implies that the human kidneys are harmed and unable to
blood filter in the manner which they should. The disease is designated “chronic” in light of …

Comprehensive performance assessment of deep learning models in early prediction and risk identification of chronic kidney disease

S Akter, A Habib, MA Islam, MS Hossen… - IEEE …, 2021 - ieeexplore.ieee.org
The incidence of chronic kidney disease (CKD) is rising rapidly around the globe.
Asymptomatic CKD is common and guideline-directed monitoring to predict CKD by various …