ArticleOphthalmology and therapy2023
Approval and Certification of Ophthalmic AI Devices in the European Union.
Article in Ophthalmology and therapy, 2023. 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.
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Who cites it
19 citing papers in PubMed.
- Challenges and Recommendations in Regulating AI Medical Devices in the European Union: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Optimizing arthroplasty outcomes: the impact of artificial intelligence and robotic assistance.Annals of medicine and surgery (2012) · 2026Review
- Customizing AI-based screening with real-world data: Practical insights from diabetic retinopathy.Acta ophthalmologica · 2026Observational
- Selecting the Right AI Algorithm for the Job: A Guide for Navigating the AI Jungle in Ophthalmology.Ophthalmology and therapy · 2025Article
- Comparison of Validity and Reliability of Manual Consensus Grading vs. Automated AI Grading for Diabetic Retinopathy Screening in Oslo, Norway: A Cross-Sectional Pilot Study.Journal of clinical medicine · 2025Article
- A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America.NPJ digital medicine · 2025Article
- Artificial intelligence in managing retinal disease-current concepts and relevant aspects for health care providers.Wiener medizinische Wochenschrift (1946) · 2025Review
- [EyeMatics-Multicenter data evaluation of real-world data with interoperable medical informatics].Die Ophthalmologie · 2025Review
- The evolution of diabetic retinopathy screening.Eye (London, England) · 2025Review
- Lights and Shadows on Artificial Intelligence in Glaucoma: Transforming Screening, Monitoring, and Prognosis.Journal of clinical medicine · 2025Review
- Shaping the Future of Healthcare: Ethical Clinical Challenges and Pathways to Trustworthy AI.Journal of clinical medicine · 2025Article
- Artificial Intelligence to Diagnose Complications of Diabetes.Journal of diabetes science and technology · 2025Review
- Diagnostic Accuracy of Automated Diabetic Retinopathy Image Assessment Software: IDx-DR and RetCAD.Ophthalmology and therapy · 2025Article
- Modern Approach to Diabetic Retinopathy Diagnostics.Diagnostics (Basel, Switzerland) · 2024Review
- Retina Fundus Photograph-Based Artificial Intelligence Algorithms in Medicine: A Systematic Review.Ophthalmology and therapy · 2024Review
- Advances in Structural and Functional Retinal Imaging and Biomarkers for Early Detection of Diabetic Retinopathy.Biomedicines · 2024Review
- AI as a Medical Device for Ophthalmic Imaging in Europe, Australia, and the United States: Protocol for a Systematic Scoping Review of Regulated Devices.JMIR research protocols · 2024Article
- Artificial Intelligence and Diabetic Retinopathy: AI Framework, Prospective Studies, Head-to-head Validation, and Cost-effectiveness.Diabetes care · 2023Review
- Artificial Intelligence Software for Diabetic Eye Screening: Diagnostic Performance and Impact of Stratification.Journal of clinical medicine · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI)-based medical devices are already commercially available in Europe. The regulations surrounding the introduction and use of medical AI devices in the European Union (EU) are different to those in the USA, and the specifics of European legislature in medical AI are not commonly known. European law classifies medical devices into four classes: I, IIa, IIb, and III, depending on the perceived risk level of the device. Medical devices are certified under independent nongovernment bodies, and some can even self-certify their compliance with EU standards. The European "open" approach is vastly different from the strict perspective of the FDA, as reflected by the number of available medical AI devices. The EU is currently in a transitory period between two regulations, further complicating the legislative landscape. The devices in question deal with extremely sensitive data, collecting, processing, and sending images and diagnoses over the internet. The EU approach puts a large burden of verifying the effectiveness and integrity of the AI device on the consumer, without giving consumers many tools to do that effectively. This highlights the need for effective legislation and oversight from governing bodies, as well as the need for understanding the legalities and limitations of AI devices for those implementing them in clinical practice.
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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.