[HTML][HTML] A survey of machine learning in kidney disease diagnosis

J Qezelbash-Chamak, S Badamchizadeh… - Machine Learning with …, 2022 - Elsevier
Applications of Machine learning (ML) in health informatics have gained increasing
attention. The timely diagnosis of kidney disease and the subsequent immediate response …

[HTML][HTML] Smart healthcare disease diagnosis and patient management: Innovation, improvement and skill development

A Ray, AK Chaudhuri - Machine Learning with Applications, 2021 - Elsevier
Data mining (DM) is an instrument of pattern detection and retrieval of knowledge from a
large quantity of data. Many robust early detection services and other health-related …

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 …

Intelligent diagnostic prediction and classification system for chronic kidney disease

M Elhoseny, K Shankar, J Uthayakumar - Scientific reports, 2019 - nature.com
At present times, healthcare systems are updated with advanced capabilities like machine
learning (ML), data mining and artificial intelligence to offer human with more intelligent and …

[HTML][HTML] Fuzzy logic-based systems for the diagnosis of chronic kidney disease

G Murugesan, TI Ahmed, J Bhola… - BioMed Research …, 2022 - ncbi.nlm.nih.gov
Kidney failure occurs whenever the kidney stops to operate properly and would be unable to
cleanse or refine the bloodstream as it should. Chronic kidney disease (CKD) is a potentially …

Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP

MJ Raihan, MAM Khan, SH Kee, AA Nahid - Scientific Reports, 2023 - nature.com
Chronic kidney disease (CKD) is a condition distinguished by structural and functional
changes to the kidney over time. Studies show that 10% of adults worldwide are affected by …

Predicting chronic kidney disease using hybrid machine learning based on apache spark

MA Abdel-Fattah, NA Othman… - Computational …, 2022 - Wiley Online Library
Chronic kidney disease (CKD) has become a widespread disease among people. It is
related to various serious risks like cardiovascular disease, heightened risk, and end‐stage …

Predicting chronic kidney disease using machine learning algorithms

A Farjana, FT Liza, PP Pandit, MC Das… - 2023 IEEE 13th …, 2023 - ieeexplore.ieee.org
In the modern era, everyone tries to be aware of their health, but because of their workload
and hectic schedules, they only pay attention to it when certain symptoms appear. However …

Chronic kidney disease prediction using boosting techniques based on clinical parameters

SM Ganie, PK Dutta Pramanik, S Mallik, Z Zhao - Plos one, 2023 - journals.plos.org
Chronic kidney disease (CKD) has become a major global health crisis, causing millions of
yearly deaths. Predicting the possibility of a person being affected by the disease will allow …

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 …