ReviewJournal of translational medicine2025
An In-depth overview of artificial intelligence (AI) tool utilization across diverse phases of organ transplantation.
Review in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Effectiveness of an artificial intelligence-assisted training program on cleaning competency among hospital environmental service staff.BMC health services research · 2026Trial
- The Anatomical Landscape of Living Donor Livers: A 101-Case Retrospective Single-Center Study in Indonesia From 2010 to 2025.Annals of transplantation · 2026Article
- Recommendations From the Implementation Steering Group for Organ Utilisation Histocompatibility and Immunogenetics Sub-Group: ISOU H&I Sub-Group Recommendations.International journal of immunogenetics · 2026Review
- An index system for evaluating the data security in trauma centers: a modified Delphi study in China.Journal of translational internal medicine · 2026Article
- Next-Generation Strategies for Neural Repair and Regeneration: Neural Organoid Transplantation in the CNS.Cell proliferation · 2026Review
- Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence-A Roadmap for Workflow-Integrated Care.Journal of clinical medicine · 2026Review
- Protocol for a global electronic Delphi on integrating artificial intelligence into solid organ transplantation.World journal of transplantation · 2026Review
- Self-driving bioprinting laboratories.Biofabrication · 2026Review
- Artificial Intelligence and Predictive Modelling for Precision Dosing of Immunosuppressants in Kidney Transplantation.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Immune cell dynamics and cytokine regulation in cornea and transplantation.Frontiers in immunology · 2026Review
- Current and Future Applications of AI-Driven Predictive Modeling and a Proposed Framework for AI-Bioprognostics in Kidney Care.Risk management and healthcare policy · 2026Review
- Towards Personalized Tacrolimus Dosing Using an Algorithm-Driven Prediction Pipeline for Kidney Transplant.Drug design, development and therapy · 2026Article
- A dialectical lens for AI and medical humanities: advancing responsible augmented humanism in Digital Public Health.Frontiers in public health · 2026Review
- From thresholds to trajectories: a perspective on reframing alloimmune risk for computational modeling in solid organ transplantation.Frontiers in immunology · 2026Review
- Artificial Intelligence Application in Cornea and External Diseases.Diagnostics (Basel, Switzerland) · 2025Review
- Review
- Artificial Intelligence in the Management of Infectious Diseases in Older Adults: Diagnostic, Prognostic, and Therapeutic Applications.Biomedicines · 2025Review
- CRISPR and Artificial Intelligence in Neuroregeneration: Closed-Loop Strategies for Precision Medicine, Spinal Cord Repair, and Adaptive Neuro-Oncology.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) offers a revolutionary approach to improve decision-making in medicine through the use of advanced computational tools. Its ability to analyze large and complex datasets enables a thorough evaluation of multiple factors, leading to a deeper understanding of medical procedures. Numerous studies have demonstrated that AI has made significant advancements in areas such as organ allocation, donor-recipient matching, and immunosuppression protocols in organ transplantation. The transplantation process consists of three key stages: pre-transplant evaluation, the surgical procedure, and post-transplant management. AI can enhance all three stages by analyzing and integrating data from histopathological reports, lab results, radiological features, and patient demographics to aid in matching donors and recipients. Additionally, AI supports robotic-assisted surgery and optimizes post-transplant regimens while evaluating complications. Various researches have utilized machine learning (ML) to predict medication bioavailability immediately after transplantation and assess the risk of post-transplant complications based on factors like genetic phenotypes, age, gender, and body mass index. This review aims to gather information on AI applications across various stages of organ transplantation and elaborate the strategies and tools relevant to these processes.
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.