ArticleFrontiers in medicine2022
Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective.
Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 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.
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Who cites it
26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 53 citations in OpenAlex.
- Trust in Artificial Intelligence-Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Facilitators and Barriers to Implementing AI in Routine Medical Imaging: Systematic Review and Qualitative Analysis.Journal of medical Internet research · 2025Pooled it
- The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: systematic review and recommendations.Implementation science : IS · 2025Pooled it
- Comprehensive recommendations for the implementation of artificial intelligence in healthcare: a narrative review on facilitators and barriers.BMJ open quality · 2026Review
- Regulation of clinical Artificial Intelligence (AI) in the Age of Agents: Unconfined Non-Deterministic Clinical Software (UNDCS) systems for healthcare.NPJ digital medicine · 2026Article
- Perceived Trust in Artificial Intelligence in Eye Care: Demographic Determinants and Variations in Attitudes Among Ophthalmologists and Residents.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
- Sociotechnical influences on the adoption and use of AI-enabled clinical decision support systems in ophthalmology: a theory-based interview study.BMC health services research · 2025Article
- Artificial Intelligence in Ophthalmology: Acceptance, Clinical Integration, and Educational Needs in Switzerland.Journal of clinical medicine · 2025Article
- Enhancement of Optical Coherence Tomography Images Using Adversarial Neural Networks: Impacts on Ophthalmic Practice.Cureus · 2025Article
- The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis.Eye (London, England) · 2025Review
- Barriers to and facilitators of clinician acceptance and use of artificial intelligence in healthcare settings: a scoping review.BMJ open · 2025Article
- Artificial Intelligence-Based Software as a Medical Device (AI-SaMD): A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Stakeholder Attitudes on AI Integration in Ophthalmology.Klinische Monatsblatter fur Augenheilkunde · 2025Review
- Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.Nature communications · 2025Article
- AI testing, evaluation, verification and validation for accessibility: a comprehensive framework.Frontiers in digital health · 2025Article
- Tackling visual impairment: emerging avenues in ophthalmology.Frontiers in medicine · 2025Review
- Review
- Liability of Health Professionals Using Sensors, Telemedicine and Artificial Intelligence for Remote Healthcare.Sensors (Basel, Switzerland) · 2024Review
- Article
- Behind the mask: a critical perspective on the ethical, moral, and legal implications of AI in ophthalmology.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
44 authors at 20 institutions in 14 countries.
Funding
Abstract
Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.
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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.