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 …
approximately 10% of the world adult population. CKD is a disorder that disrupts normal …
[HTML][HTML] Performance analysis of cost-sensitive learning methods with application to imbalanced medical data
Many real-world machine learning applications require building models using highly
imbalanced datasets. Usually, in medical datasets, the healthy patients or samples are …
imbalanced datasets. Usually, in medical datasets, the healthy patients or samples are …
Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques
Software defect prediction (SDP) in the initial period of the software development life cycle
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
Comprehensive performance assessment of deep learning models in early prediction and risk identification of chronic kidney disease
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 …
Asymptomatic CKD is common and guideline-directed monitoring to predict CKD by various …
A comprehensive unsupervised framework for chronic kidney disease prediction
The incidence, prevalence, and progression of chronic kidney disease (CKD) conditions
have evolved over time, especially in countries that have varied social determinants of …
have evolved over time, especially in countries that have varied social determinants of …
Performance analysis of chronic kidney disease through machine learning approaches
Data mining and machine learning play a vital role in health care and also medical
information and detection, Now a day machine learning techniques use awareness of some …
information and detection, Now a day machine learning techniques use awareness of some …
Health data-driven machine learning algorithms applied to risk indicators assessment for chronic kidney disease
Purpose As global aging progresses, the health management of chronic diseases has
become an important issue of concern to governments. Influenced by the aging of its …
become an important issue of concern to governments. Influenced by the aging of its …
Empirical assessment of machine learning techniques for software requirements risk prediction
Software risk prediction is the most sensitive and crucial activity of Software Development
Life Cycle (SDLC). It may lead to the success or failure of a project. The risk should be …
Life Cycle (SDLC). It may lead to the success or failure of a project. The risk should be …
Enhanced prediction of chronic kidney disease using feature selection and boosted classifiers
Chronic kidney disease (CKD) is a widespread illness affecting humans globally. It poses a
significant challenge for societies and global health care systems. Specialized screening …
significant challenge for societies and global health care systems. Specialized screening …
Development of a predictive analytic system for chronic kidney disease using ensemble-based machine learning
Z Hasan, RR Khan, W Rifat, DS Dipu… - … Science of Riga …, 2021 - ieeexplore.ieee.org
Chronic kidney disease (CKD) is one of the severe diseases in which kidney functions are
lost gradually over months to years. Though, in the early stages of CKD little to no symptoms …
lost gradually over months to years. Though, in the early stages of CKD little to no symptoms …