ReviewAnnals of biomedical engineering2023
Generative Adversarial Networks in Medicine: Important Considerations for this Emerging Innovation in Artificial Intelligence.
Review in Annals of biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis 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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ophthalmic Image Synthesis and Analysis with Generative Adversarial Network Artificial Intelligence.Journal of imaging informatics in medicine · 2026Pooled it
- Graph Neural Networks in Neuroimaging: Current Status and Biostatistical Considerations for Clinical Deployment.Annals of biomedical engineering · 2026Review
- Ethical and Governance Challenges of AI in Medical Imaging and Diagnostics: A Systematic Survey and Policy Framework Recommendations.Healthcare (Basel, Switzerland) · 2026Review
- Chemometric Methods Applied to Infrared and Raman Spectroscopy for Arboviruses Diagnosis: A Systematic Review With Meta-Analysis.Analytical science advances · 2025Review
- OpenAI's Sora in medical education: artificial videos in the classroom of the future Sora d'OpenAI dans l'enseignement médical : des vidéos artificielles dans la salle de classe du futur.Canadian medical education journal · 2025Article
- Generative Adversarial Networks in Dermatology: A Narrative Review of Current Applications, Challenges, and Future Perspectives.Bioengineering (Basel, Switzerland) · 2025Review
- Intelligence Architectures and Machine Learning Applications in Contemporary Spine Care.Bioengineering (Basel, Switzerland) · 2025Review
- Applications of generative adversarial networks in the diagnosis, prognosis, and treatment of ophthalmic diseases.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Review
- Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.Neuroinformatics · 2025Article
- Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care.Diagnostics (Basel, Switzerland) · 2025Review
- The visual communication using generative artificial intelligence in the context of new media.Scientific reports · 2025Article
- The clinical implications and interpretability of computational medical imaging (radiomics) in brain tumors.Insights into imaging · 2025Review
- Applications of Machine Learning-Driven Molecular Models for Advancing Ophthalmic Precision Medicine.Bioengineering (Basel, Switzerland) · 2025Review
- Perfusion Parameter Map Generation from 3 Phases of Computed Tomography Perfusion in Stroke Using Generative Adversarial Networks.Research (Washington, D.C.) · 2025Article
- Deep learning architectures for influenza dynamics and treatment optimization: a comprehensive review.Frontiers in artificial intelligence · 2025Review
- Ethics of AI in healthcare: a scoping review demonstrating applicability of a foundational framework.Frontiers in digital health · 2025Review
- Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.Sensors (Basel, Switzerland) · 2024Article
- Quantum biology in ophthalmology.Eye (London, England) · 2024Article
- Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist.The Lancet. Digital health · 2024Article
- OpenAI's Sora in ophthalmology: revolutionary generative AI in eye health.Eye (London, England) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations. With these powerful applications, there is a necessity for framework regulations to ensure equitable and safe deployment of technology. Generative Adversarial Networks (GANs) are emerging ML techniques that have immense applications in medical imaging due to their ability to produce synthetic medical images and aid in medical AI training. Producing accurate synthetic images with GANs can address current limitations in AI development for medical imaging and overcome current dataset type and size constraints. Offsetting these constraints can dramatically improve the development and implementation of AI medical imaging and restructure the practice of medicine. As observed with its other AI predecessors, considerations must be taken into place to help regulate its development for clinical use. In this paper, we discuss the legal, ethical, and technical challenges for future safe integration of this technology in the healthcare sector.
Indexed as
Identifiers
37488468What 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.