ReviewInternational journal of medical sciences2020
Role of Artificial Intelligence in Kidney Disease.
Review in International journal of medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 citations in OpenAlex.
- Applications of artificial intelligence algorithms in ultrasound-based kidney stone detection, classification, prediction, and management: a systematic review.Abdominal radiology (New York) · 2026Pooled it
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- Integrating artificial intelligence in healthcare: applications, challenges, and future directions.Future science OA · 2025Review
- Recent advancements in patented technologies for the diagnosis and treatment of chronic kidney disease.International urology and nephrology · 2025Review
- Ethics of Personalised Medicine: Importance of the Multidisciplinary Approach in KidneySign Project.Proteomics · 2025Article
- Contemporary Perspectives on Chronic Renal Disorders.Chronic diseases and translational medicine · 2025Review
- Emerging Biomarkers and Advanced Diagnostics in Chronic Kidney Disease: Early Detection Through Multi-Omics and AI.Diagnostics (Basel, Switzerland) · 2025Review
- Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.Scientific reports · 2025Article
- Synthetic data as an investigative tool in hypertension and renal diseases research.World journal of methodology · 2025Article
- Article
- New approaches to acute kidney injury.Clinical kidney journal · 2024Article
- AI-Driven Patient Education in Chronic Kidney Disease: Evaluating Chatbot Responses against Clinical Guidelines.Diseases (Basel, Switzerland) · 2024Article
- Machine learning-based diagnosis and prognosis of IgAN: A systematic review and meta-analysis.Heliyon · 2024Review
- Review
- Numerical Simulation of Mass Transfer in Hollow Fiber Membrane Module for Membrane-Based Artificial Organs.Membranes · 2024Article
- Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review.Journal of clinical medicine · 2024Review
- Artificial Intelligence in Kidney Disease: A Comprehensive Study and Directions for Future Research.Diagnostics (Basel, Switzerland) · 2024Review
- AI-Powered Renal Diet Support: Performance of ChatGPT, Bard AI, and Bing Chat.Clinics and practice · 2023Article
- Predicting outcomes of continuous renal replacement therapy using body composition monitoring: a deep-learning approach.Scientific reports · 2023Article
- Machine Learning Models to Predict the Risk of Rapidly Progressive Kidney Disease and the Need for Nephrology Referral in Adult Patients with Type 2 Diabetes.International journal of environmental research and public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied to early detections, disease diagnoses, and management. Owing to the huge number of patients, kidney disease remains a global health problem. Challenges remain in its diagnosis and treatment. AI could take individual conditions into account, produce suitable decisions and promise to make great strides in kidney disease management. Here, we review the current studies of AI applications in kidney disease in alerting systems, diagnostic assistance, guiding treatment and evaluating prognosis. Although the number of studies related to AI applications in kidney disease is small, the potential of AI in the management of kidney disease is well recognized by clinicians; AI will greatly enhance clinicians' capacity in their clinical practice in the future.
Indexed as
Identifiers
What OpenQuestion holds
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.