ReviewWorld journal of transplantation2021
Artificial intelligence and kidney transplantation.
Review in World journal of transplantation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
19 citing papers in PubMed, 30 citations in OpenAlex.
- Exfoliated kidney cells from urine for non-invasive kidney transplant monitoring: A potential opportunity?Clinical and experimental nephrology · 2026Review
- Human-AI Interaction in Kidney Transplant Decision Support Systems: Qualitative Study of Patient and Support Person Expectations.Journal of medical Internet research · 2026Article
- Construction of a deep learning-based predictive model for delayed graft function in kidney transplantation.Current urology · 2026Article
- Multimodal deep learning integration for predicting renal function outcomes in living donor kidney transplantation: a retrospective cohort study.International journal of surgery (London, England) · 2026Article
- Review
- An In-depth overview of artificial intelligence (AI) tool utilization across diverse phases of organ transplantation.Journal of translational medicine · 2025Review
- Synthetic data as an investigative tool in hypertension and renal diseases research.World journal of methodology · 2025Article
- Improving kidney transplant care through the application of continuous glucose monitoring - a narrative review.Frontiers in nephrology · 2025Review
- The Use of Machine Learning in the Diagnosis of Kidney Allograft Rejection: Current Knowledge and Applications.Diagnostics (Basel, Switzerland) · 2024Review
- Artificial intelligence and predictive models for early detection of acute kidney injury: transforming clinical practice.BMC nephrology · 2024Review
- Present and Future Applications of Artificial Intelligence in Kidney Transplantation.Journal of clinical medicine · 2024Review
- Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor-Recipient Matching.Diagnostics (Basel, Switzerland) · 2024Article
- Revisiting pre-transplant preparation to optimize long-term kidney transplant outcomes.Journal of nephrology · 2024Article
- Beyond Human Limits: Harnessing Artificial Intelligence to Optimize Immunosuppression in Kidney Transplantation.Journal of clinical medicine research · 2023Review
- Developing supervised machine learning algorithms to evaluate the therapeutic effect and laboratory-related adverse events of cyclosporine and tacrolimus in renal transplants.International journal of clinical pharmacy · 2023Article
- Prediction tool for renal adaptation after living kidney donation using interpretable machine learning.Frontiers in medicine · 2023Article
- Artificial Intelligence in Acute Kidney Injury Prediction.Advances in chronic kidney disease · 2022Review
- The state of the art for artificial intelligence in lung digital pathology.The Journal of pathology · 2022Review
- Bioethical challenges in the integration of artificial intelligence in transplant surgery 4.0: A scoping review.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence and its primary subfield, machine learning, have started to gain widespread use in medicine, including the field of kidney transplantation. We made a review of the literature that used artificial intelligence techniques in kidney transplantation. We located six main areas of kidney transplantation that artificial intelligence studies are focused on: Radiological evaluation of the allograft, pathological evaluation including molecular evaluation of the tissue, prediction of graft survival, optimizing the dose of immunosuppression, diagnosis of rejection, and prediction of early graft function. Machine learning techniques provide increased automation leading to faster evaluation and standardization, and show better performance compared to traditional statistical analysis. Artificial intelligence leads to improved computer-aided diagnostics and quantifiable personalized predictions that will improve personalized patient care.
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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.