ReviewAdvances in chronic kidney disease2022
Artificial Intelligence in Acute Kidney Injury Prediction.
Review in Advances in chronic kidney disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- Nephrology 2050: an evidence-informed roadmap from precision prevention to kidney regeneration.International urology and nephrology · 2026Review
- Artificial intelligence for predicting paediatric acute kidney injury: a systematic review and meta-analysis.Clinical kidney journal · 2026Article
- Postoperative complications of coronary artery bypass grafting: a narrative review on pathophysiology, management strategies, and the emerging role of artificial intelligence.Cardiovascular diagnosis and therapy · 2026Review
- Predicting Acute Kidney Injury with Nephrotoxic Burden in Noncritical Patients: An Internal and External Validation Study.Kidney360 · 2026Article
- Aligning Artificial Intelligence Prediction Targets with Clinical Workflows Using Human Centered Design Methods.medRxiv : the preprint server for health sciences · 2026Article
- MLP-CKD: a clinically informed deep learning framework for admission laboratory-based screening and risk stratification of uremia-associated advanced renal dysfunction.Frontiers in public health · 2026Article
- Development of a risk calculator for acute kidney injury in trauma patients: an experimental study.Trauma surgery & acute care open · 2026Article
- Understanding the Risks and Benefits of Implementing AI-Enabled Remote Patient Monitoring Systems for Disease Management.International journal of environmental research and public health · 2025Article
- Machine Learning Models for Point-of-Care Diagnostics of Acute Kidney Injury.Diagnostics (Basel, Switzerland) · 2025Article
- Predicting Acute Kidney Injury in Acute Rhabdomyolysis.Journal of clinical medicine · 2025Article
- Development of a neural network model for early detection of creatinine change in critically Ill children.Frontiers in pediatrics · 2025Article
- Artificial intelligence and pediatric acute kidney injury: a mini-review and white paper.Frontiers in nephrology · 2025Review
- Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic Review.Kidney medicine · 2025Review
- Artificial Intelligence and ChatGPT in Medical Education: A Cross-Sectional Questionnaire on students' Competence.Journal of CME · 2025Article
- New approaches to acute kidney injury.Clinical kidney journal · 2024Article
- TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Encompassing trust in medical AI from the perspective of medical students: a quantitative comparative study.BMC medical ethics · 2024Article
- Risk prediction models for successful discontinuation in acute kidney injury undergoing continuous renal replacement therapy.iScience · 2024Article
- Optimizing artificial intelligence in sepsis management: Opportunities in the present and looking closely to the future.Journal of intensive medicine · 2024Review
- Artificial Intelligence in Nephrology: Pioneering Precision with Multimodal Intelligence.Indian journal of nephrologyReview
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The use of artificial intelligence (AI) in nephrology and its associated clinical research is growing. Recent years have seen increased interest in utilizing AI to predict the development of hospital-based acute kidney injury (AKI). Several AI techniques have been employed to improve the ability to detect AKI across a variety of hospitalized settings. This review discusses the evolutions of AKI risk prediction discussing the static risk assessment models of yesteryear as well as the more recent trend toward AI and advanced learning techniques. We discuss the relative improvement in AKI detection as well as the relative dearth of data around the clinical implementation and patient outcomes using these models. The use of AI for AKI detection and clinical care is in its infancy, and this review describes how we arrived at our current position and hints at the promise of the future.
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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.