ArticleHealth information science and systems2024
Deep-kidney: an effective deep learning framework for chronic kidney disease prediction.
Article in Health information science and systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Bioinspired hybrid optimisation and deep belief neural networks for early chronic kidney disease detection: an explainable clinical AI framework.Renal failure · 2026Article
- Machine Learning and Deep Learning for Early Disease Detection Across Modalities: A Comprehensive Review of Methods, Applications, and Clinical Translation.Diagnostics (Basel, Switzerland) · 2026Review
- GERBEHRT: a BERT-based model tailored for German electronic health records - potential in chronic kidney disease prediction.BMC medical informatics and decision making · 2026Article
- A Risk-Oriented and Explainable Hierarchical AI Framework for Chronic Kidney Disease Classification.Diagnostics (Basel, Switzerland) · 2026Article
- Detection and classification of medical images using deep learning for chronic kidney disease.International urology and nephrology · 2026Article
- Development and evaluation of an AI-based prediction model for chronic kidney disease after cardiac surgery.BMJ digital health & AI · 2026Article
- The impact of the COVID-19 pandemic on the global burden of mental disorders: a counterfactual modeling study from 1990 to 2021.Translational psychiatry · 2025Article
- Stacking ensemble model for predicting chronic kidney disease in the Uddanam region of India with unknown etiology.Scientific reports · 2025Article
- Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches.European journal of medical research · 2025Review
- Kidney Disease Segmentation and Classification Using Firefly Sigma Seeker and MagWeight Rank Techniques.Bioengineering (Basel, Switzerland) · 2025Article
- Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging.Scientific reports · 2025Article
- An attention enhanced dilated bottleneck network for kidney disease classification.Scientific reports · 2025Article
- Early prediction of CKD from time series data using adaptive PSO optimized echo state networks.Scientific reports · 2025Article
- A non-invasive prediction model for coronary artery stenosis severity based on multimodal data.Frontiers in physiology · 2025Article
- Novel statistically equivalent signature-based hybrid feature selection and ensemble deep learning LSTM and GRU for chronic kidney disease classification.PeerJ. Computer science · 2024Article
Corrections and comments
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Chronic kidney disease (CKD) is one of today's most serious illnesses. Because this disease usually does not manifest itself until the kidney is severely damaged, early detection saves many people's lives. Therefore, the contribution of the current paper is proposing three predictive models to predict CKD possible occurrence within 6 or 12 months before disease existence namely; convolutional neural network (CNN), long short-term memory (LSTM) model, and deep ensemble model. The deep ensemble model fuses three base deep learning classifiers (CNN, LSTM, and LSTM-BLSTM) using majority voting technique. To evaluate the performance of the proposed models, several experiments were conducted on two different public datasets. Among the predictive models and the reached results, the deep ensemble model is superior to all the other models, with an accuracy of 0.993 and 0.992 for the 6-month data and 12-month data predictions, respectively.
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