ArticleJournal of healthcare engineering2021
Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
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Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 232 citations in OpenAlex.
- Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.Journal of nephrology · 2023Pooled it
- PCSA-Net: pyramid channel and spatial attention network for multiclass renal disease diagnosis using CT images.Scientific reports · 2026Article
- Artificial Intelligence in Nephrology: From Early Detection to Clinical Management of Kidney Diseases.Bioengineering (Basel, Switzerland) · 2025Review
- Developing multimodal cervical cancer risk assessment and prediction model based on LMIC hospital patient card sheets and histopathological images.BMC medical informatics and decision making · 2025Article
- Fused federated learning framework for secure and decentralized patient monitoring in healthcare 5.0 using IoMT.Scientific reports · 2025Article
- Application of radiofrequency features in the diagnosis of severity of fatty liver disease.European journal of medical research · 2025Article
- MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction.MethodsX · 2025Article
- Synergistic feature selection and distributed classification framework for high-dimensional medical data analysis.MethodsX · 2025Article
- Improved CKD classification based on explainable artificial intelligence with extra trees and BBFS.Scientific reports · 2025Article
- Advanced Deep Learning and Machine Learning Techniques for MRI Brain Tumor Analysis: A Review.Sensors (Basel, Switzerland) · 2025Review
- A teaching proposal for a short course on biomedical data science.PLoS computational biology · 2025Article
- Leveraging machine learning for precision medicine: a predictive model for cognitive impairment in cholestasis patients.BMC gastroenterology · 2025Article
- Construction of an intelligent screening model for allergic rhinitis based on routine blood tests.PloS one · 2025Article
- Variational quantum classifier-based early identification and classification of chronic kidney disease using sparse autoencoder and LASSO shrinkage.PeerJ. Computer science · 2025Article
- Prevalence and Data-Driven Exploration of Pre-Diagnostic Symptoms and Features of Gilbert's Syndrome in the UK Primary Care Population.Clinical epidemiology · 2025Article
- Development of risk models for early detection and prediction of chronic kidney disease in clinical settings.Scientific reports · 2024Article
- Artificial neural network-based prediction of multiple sclerosis using blood-based metabolomics data.Multiple sclerosis and related disorders · 2024Article
- Deep-kidney: an effective deep learning framework for chronic kidney disease prediction.Health information science and systems · 2024Article
- Cranial bone thickness and density anomalies quantified from CT images can identify chronic increased intracranial pressure.Neuroradiology · 2024Article
- An optimized method for mulberry silkworm, Bombyx mori (Bombycidae:Lepidoptera) sex classification using TLBPSGA-RFEXGBoost.Biology open · 2024Article
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 kidney function. Due to the increasing number of people with CKD, effective prediction measures for the early diagnosis of CKD are required. The novelty of this study lies in developing the diagnosis system to detect chronic kidney diseases. This study assists experts in exploring preventive measures for CKD through early diagnosis using machine learning techniques. This study focused on evaluating a dataset collected from 400 patients containing 24 features. The mean and mode statistical analysis methods were used to replace the missing numerical and the nominal values. To choose the most important features, Recursive Feature Elimination (RFE) was applied. Four classification algorithms applied in this study were support vector machine (SVM),
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.