ReviewTaiwan journal of ophthalmology
Artificial intelligence and digital solutions for myopia.
Review in Taiwan journal of ophthalmology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 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
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Artificial intelligence in pathologic myopia: a review of clinical research studies.Frontiers in medicine · 2025Pooled it
- Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature.Frontiers in medicine · 2025Pooled it
- Emerging Technologies for the Management and Mitigation of Myopia Progression: A Scoping Review.Health science reports · 2026Article
- Article
- From vision correction to health promotion: a public health approach to myopia.Frontiers in public health · 2026Article
- Benchmark analysis of myopia-related issues using large language models: a comparison of ChatGPT-4o and deepseek.BMC ophthalmology · 2025Article
- Integrating Artificial Intelligence Into Telemedicine: Evidence, Challenges, and Future Directions.Cureus · 2025Review
- IMI-Instrumentation for Myopia Management.Investigative ophthalmology & visual science · 2025Review
- Application of artificial intelligence in myopia prevention and control.Pediatric investigation · 2025Review
- Efficacy of Myopia Prevention in At-Risk Children: A Systematic Review and Network Meta-Analysis.Journal of clinical medicine · 2025Review
- Application of the precision eye health education model in myopia prevention and control in adolescents.Frontiers in pediatrics · 2025Article
- Global trends and hotspots in artificial intelligence for high myopia: a bibliometric analysis.Frontiers in medicine · 2025Article
- New Horizons in Myopia Management: Bridging Epidemiology and Clinical Innovation.Vision (Basel, Switzerland) · 2024Article
- Review
- Bridging the Gap: Exploring Opportunities, Challenges, and Problems in Integrating Assistive Technologies, Robotics, and Automated Machines into theHealthcare (Basel, Switzerland) · 2023Article
- Role of artificial intelligence in optical coherence tomography in myopia and pathological myopia.Taiwan journal of ophthalmologyReview
- The power of big data and artificial intelligence in ophthalmology.Taiwan journal of ophthalmologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Myopia as an uncorrected visual impairment is recognized as a global public health issue with an increasing burden on health-care systems. Moreover, high myopia increases one's risk of developing pathologic myopia, which can lead to irreversible visual impairment. Thus, increased resources are needed for the early identification of complications, timely intervention to prevent myopia progression, and treatment of complications. Emerging artificial intelligence (AI) and digital technologies may have the potential to tackle these unmet needs through automated detection for screening and risk stratification, individualized prediction, and prognostication of myopia progression. AI applications in myopia for children and adults have been developed for the detection, diagnosis, and prediction of progression. Novel AI technologies, including multimodal AI, explainable AI, federated learning, automated machine learning, and blockchain, may further improve prediction performance, safety, accessibility, and also circumvent concerns of explainability. Digital technology advancements include digital therapeutics, self-monitoring devices, virtual reality or augmented reality technology, and wearable devices - which provide possible avenues for monitoring myopia progression and control. However, there are challenges in the implementation of these technologies, which include requirements for specific infrastructure and resources, demonstrating clinically acceptable performance and safety of data management. Nonetheless, this remains an evolving field with the potential to address the growing global burden of myopia.
Indexed as
Identifiers
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.