ArticleFuture healthcare journal2022
Generative adversarial networks and synthetic patient data: current challenges and future perspectives.
Article in Future healthcare journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled it.
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
50 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Ophthalmic Image Synthesis and Analysis with Generative Adversarial Network Artificial Intelligence.Journal of imaging informatics in medicine · 2026Pooled it
- Current Applications of Artificial Intelligence for Fuchs Endothelial Corneal Dystrophy: A Systematic Review.Translational vision science & technology · 2025Pooled it
- Ethical and practical challenges of generative AI in healthcare and proposed solutions: a survey.Frontiers in digital health · 2025Pooled it
- The Accuracy and Capability of Artificial Intelligence Solutions in Health Care Examinations and Certificates: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- [Artificial intelligence in surgical disciplines: Clinical application, advantages, and potential-a Delphi expert consensus].Urologie (Heidelberg, Germany) · 2026Article
- GAN-enhanced digital twins for biomarker-guided cancer immunotherapy and adoptive cell therapy: a mini review.Frontiers in medicine · 2026Review
- Emerging Technologies for Exploring the Cellular Mechanisms in Vascular Diseases.International journal of molecular sciences · 2025Review
- Artificial Intelligence in Planning for Spine Surgery.Current reviews in musculoskeletal medicine · 2025Review
- Clinical Assessment of Fine-Tuned Open-Source LLMs in Cardiology: From Progress Notes to Discharge Summary.Journal of healthcare informatics research · 2025Article
- AI-driven Technologies for Wrist Fracture Prediction: A Narrative Review of Emerging Approaches.Journal of wrist surgery · 2025Article
- A stomata imaging and segmentation pipeline incorporating generative AI to reduce dependency on manual groundtruthing.Plant methods · 2025Article
- Article
- In Vitro Skin Models as Non-Animal Methods for Dermal Drug Development and Safety Assessment.Pharmaceutics · 2025Review
- Bridging generative AI and healthcare practice: insights from the GenAI Health Hackathon at Hospital Clínic de Barcelona.BMJ health & care informatics · 2025Article
- Generative artificial intelligence in medicine.Nature medicine · 2025Review
- An enhancement of machine learning model performance in disease prediction with synthetic data generation.Scientific reports · 2025Article
- Combating Antimicrobial Resistance: Role of Key Stakeholders with Focus on the Pharmaceutical Sector.Pharmaceutical medicine · 2025Review
- Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.Neuroinformatics · 2025Article
- Potential Obstacles and Strategic Interventions for Addressing Gaps in the Understanding of Human-Artificial Intelligence Interactions in Medical Practice.Korean journal of radiology · 2025Article
- The visual communication using generative artificial intelligence in the context of new media.Scientific reports · 2025Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has been heralded as one of the key technological innovations of the 21st century. Within healthcare, much attention has been placed upon the ability of deductive AI systems to analyse large datasets to find patterns that would be unfeasible to program. Generative AI, including generative adversarial networks, are a newer type of machine learning that functions to create fake data after learning the properties of real data. Artificially generated patient data has the potential to revolutionise clinical research and protect patient privacy. Using novel techniques, it is increasingly possible to fully anonymise datasets to the point where no datapoint is traceable to any real individual. This can be used to expand and balance datasets as well as to replace the use of real patient data in certain contexts. This paper focuses upon three key uses of synthetic data: clinical research, data privacy and medical education. We also highlight ethical and practical concerns that require consideration.
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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.