ReviewHealth care science2026
Artificial Intelligence in Ophthalmology: Current Status, Challenges, and Future Perspectives.
Review in Health care science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is revolutionizing ophthalmology by providing innovative solutions for disease screening, diagnosis, personalized treatment, and the delivery of global healthcare services. This review explores the current state of AI research and applications in the field of ophthalmology, and the applications of telemedicine as well as clinical trials demonstrating AI's utility in reducing diagnostic time and improving treatment outcomes. It also analyzes the challenges faced in practical applications, including economic constraints, data privacy issues, and regulatory hurdles. The review highlights the future directions of AI integration, including highly accurate AI diagnosis, the formulation of personalized treatment plans, AI-assisted surgical treatment, wearable medical devices, and telemedicine connectivity technologies. In addition, collaborative efforts among academia, the industry, and policymakers are crucial for overcoming these obstacles and fully unleashing the potential of AI in achieving equitable, efficient, and personalized ophthalmic healthcare services.
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.