ArticleScientific reports2019
Identifying progressive CKD from healthy population using Bayesian network and artificial intelligence: A worksite-based cohort study.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence in predicting chronic kidney disease prognosis. A systematic review and meta-analysis.Renal failure · 2024Pooled it
- Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.Journal of nephrology · 2023Pooled it
- Prediction of chronic kidney disease and its progression by artificial intelligence algorithms.Journal of nephrology · 2022Pooled it
- Chronic renal disease detection developments with future potential to improve veterinary clinical practice.Frontiers in veterinary science · 2026Review
- Artificial Intelligence in Nephrology: From Early Detection to Clinical Management of Kidney Diseases.Bioengineering (Basel, Switzerland) · 2025Review
- Review
- Artificial Intelligence in Nephrology: Clinical Applications and Challenges.Kidney medicine · 2025Review
- Variational quantum classifier-based early identification and classification of chronic kidney disease using sparse autoencoder and LASSO shrinkage.PeerJ. Computer science · 2025Article
- Review
- Prediction of the risk of developing end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms.BioData mining · 2023Article
- Machine-learning-based Web system for the prediction of chronic kidney disease progression and mortality.PLOS digital health · 2023Article
- Article
- Identifying risk factors of developing type 2 diabetes from an adult population with initial prediabetes using a Bayesian network.Frontiers in public health · 2022Article
- Elderly Patients in a Large Nephrology Unit: Who Are Our Old, Old-Old and Oldest-Old Patients?Journal of clinical medicine · 2021Article
- Leveraging 16S rRNA Microbiome Sequencing Data to Identify Bacterial Signatures for Irritable Bowel Syndrome.Frontiers in cellular and infection microbiology · 2021Article
- Article
- Role of Artificial Intelligence in Kidney Disease.International journal of medical sciences · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying progressive early chronic kidney disease (CKD) patients at a health checkup is a good opportunity to improve their prognosis. However, it is difficult to identify them using common health tests. This worksite-based cohort study for 7 years in Japan (n = 7465) was conducted to evaluate the progression of CKD. The outcome was aggravation of the KDIGO prognostic category of CKD 7 years later. The subjects were male, 59.1%; age, 50.1 ± 6.3 years; and eGFR, 79 ± 14.4 mL/min/1.73 m
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