SynthesisFrontiers in medicine2024
Trends and hotspots in the field of diabetic retinopathy imaging research from 2000-2023.
Synthesis in Frontiers in medicine, 2024. 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.
- An enhanced diabetic retinopathy detection approach using optimized deep learning technique.Scientific reports · 2026Article
- Early prediction of diabetic retinopathy using a multimodal deep learning framework integrating fundus and OCT imaging.Frontiers in medicine · 2025Article
- A panoramic perspective: application prospects and outlook of multimodal artificial intelligence in the management of diabetic retinopathy.Frontiers in public health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic retinopathy (DR) poses a major threat to diabetic patients' vision and is a critical public health issue. Imaging applications for DR have grown since the 21st century, aiding diagnosis, grading, and screening. This study uses bibliometric analysis to assess the field's advancements and key areas of interest. Methods: This study performed a bibliometric analysis of DR imaging articles collected from the Web of Science Core Collection database between January 1st, 2000, and December 31st, 2023. The literature information was then analyzed through CiteSpace. Results: The United States and China led in the number of publications, with 719 and 609, respectively. The University of London topped the institution list with 139 papers. Tien Yin Wong was the most prolific researcher. Invest. Ophthalmol. Vis. Sci. published the most articles (105). Notable burst keywords were "deep learning," "artificial intelligence," et al. Conclusion: The United States is at the forefront of DR research, with the University of London as the top institution and Invest. Ophthalmol. Vis. Sci. as the most published journal. Tien Yin Wong is the most influential researcher. Hotspots like "deep learning," and "artificial intelligence," have seen a significant rise, indicating artificial intelligence's growing role in DR imaging.
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.