ArticleJMIR research protocols2026
Artificial Intelligence-Assisted Screening for Patients With Diabetic Retinopathy and Age-Related Macular Degeneration in Family Medicine and Geriatric and Gerontology Care: Protocol for a Pragmatic Randomized Clinical Trial.
Article in JMIR research protocols, 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
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are 2 of the leading causes of vision loss worldwide. As population aging and diabetes prevalence increase, timely detection of these conditions has become essential. However, limited professionalism and insufficient training in ophthalmic screening among general medicine physicians may lead to delayed diagnosis and treatment. Artificial intelligence (AI)-assisted diagnostic tools may help to improve the screening of DR and AMD in routine clinical practice. Objective: This study aims to evaluate the clinical effectiveness and cost-effectiveness of AI-assisted fundus imaging for DR and AMD screening in adults with diabetes and older adults at risk of macular degeneration. Methods: This multicenter, 2-arm, parallel-group, open-label, individual-level randomized controlled trial and patient recruitment are performed at the settings of Family Medicine and Geriatric and Gerontology Care over 4 medical centers in Taiwan. Eligibility includes (1) diabetic individuals aged ≥20 years for DR screening, and (2) individuals aged ≥50 years for AMD screening. The study protocol has been approved by the ethics committees of all participating hospitals, and all participants will provide written informed consent. Results: The study was funded in September 2024, began on October 2, 2025, and is expected to be completed in December 2027. After the pilot implementation phase without randomization, participants will be randomized 1:1 into two groups: (1) AI-assisted screening, and (2) usual physician-only screening. The primary outcomes will include the detection rates (defined as participants with confirmed DR or AMD among all screened participants) and the positive predictive values (defined as participants with confirmed DR or AMD among those who tested positive). Cost-effectiveness analyses will be performed using data derived from the trial results. Conclusions: This study will provide robust evidence on the effectiveness of AI-assisted ophthalmic screening in improving patient eye health outcomes through timely screening and accurate early detection. This strategy may be cost-effective.
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.