ArticleAdvances in ophthalmology practice and research
Shaping the future of myopia with artificial intelligence: Mapping trends and promising directions.
Article in Advances in ophthalmology practice and research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Myopia management functional lenses (MMFL): a bibliometric analysis of multidisciplinary perspective and trend insights in the context of vision health.International ophthalmology · 2026Review
- Myopia as a Global Public Health Challenge a Narrative Review.Life (Basel, Switzerland) · 2026Review
- Bibliometric study on hotspots and trends of immunotherapy for kidney cancer from 2014 to 2024.Translational andrology and urology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The worldwide increase in myopia and its associated complications has sparked a growing interest in the application of artificial intelligence (AI). This study aims to provide a comprehensive bibliometric analysis of the application of AI in myopia. Methods: Articles and review articles on AI in myopia were retrieved from the Web of Science Core Collection (WoSCC). VOSviewer and CiteSpace served as the core tools for bibliometric analysis. Results: Our study included a total of 305 relevant articles, with a steady increase in publications observed from 2010 to 2024. The People's Republic of China secured the top position among the most published countries and Capital Medical University and Sun Yat-sen University emerged as the most active institutions. Xu Xun and Zhou Xingtao contributed the most papers in this area. Translational Vision Science & Technology was the most prolific journal. Keywords analysis highlighted myopia management, orthokeratology and atropine, optical coherence tomography, refractive surgery, and myopia complications as key research areas. While notable advancements have been achieved in early screening, precise diagnosis, and progression prediction of myopia, research on intervention prognosis prediction and intervention decision-making remains inadequate. Conclusions: While AI has revolutionized myopia screening and diagnosis. further investigation is needed into clinical decision-making on interventions for myopia care. Balancing intervention costs, efficacy, and side effects is critical to advancing the development of AI in myopia in the future.
Indexed as
Identifiers
What Socratic 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 Socratic graph.