ReviewMedical science monitor : international medical journal of experimental and clinical research2026
A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.
Review in Medical science monitor : international medical journal of experimental and clinical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical efficiency and manage growing patient volumes, the potential for smart technologies to streamline ophthalmic care warrants more exploration. To date, smart technologies have demonstrated potential as practical adjunctive tools that support ophthalmic referrals and clinical practice in ophthalmology. Smart technologies that support ophthalmic referrals now include CDSS that contain algorithms with the capacity to more efficiently identify suspected ophthalmic diseases that may be urgent or require prompt treatment in the primary care setting, compared with traditional referral models. These approaches also include installation of AI-powered ophthalmic imaging machines and electronic health records-analytical packages in primary care offices, where they can be used to screen for structural, historical, or symptomatic manifestations of ophthalmic diseases requiring ophthalmologist evaluation. Meanwhile, smart technologies that support ophthalmology practices include AI and big data simulations for optimized patient encounter schedules and chatbot-facilitated appointment confirmations. Amidst a smart technology renaissance, review is needed to capture existing smart technologies to inform integration in the practices of ophthalmic and general practitioners. This article aims to review the clinical utility of emerging smart technology relevant to ophthalmic referrals and ophthalmology practice.
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.