ArticleMedicine2024
Analyzing shifts in age-related macular degeneration research trends since 2014: A bibliometric study with triple-map Sankey diagrams (TMSD).
Article in Medicine, 2024. 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
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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.
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Who cites it
1 citing paper in PubMed.
- Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing.BMC medical informatics and decision making · 2025Article
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
backgroundAge-related macular degeneration (AMD) is the primary cause of vision impairment in older adults, especially in developed countries. While many articles on AMD exist in the literature, none specifically delve into the trends based on document categories. While bibliometric studies typically use dual-map overlays to highlight new trends, these can become congested and unclear with standard formats (e.g., in CiteSpace software). In this study, we introduce a unique triple-map Sankey diagram (TMSD) to assess the evolution of AMD research. Our objective is to understand the nuances of AMD articles and show the effectiveness of TMSD in determining whether AMD research trends have shifted over the past decade.
methodsWe collected 7465 articles and review pieces related to AMD written by ophthalmologists from the Web of Science core collection, accumulating article metadata from 2014 onward. To delve into the characteristics of these AMD articles, we employed various visualization methods, with a special focus on TMSD to track research evolution. We adopted the descriptive, diagnostic, predictive, and prescriptive analytics (DDPP) model, complemented by the follower-leading clustering algorithm (FLCA) for clustering analysis. This synergistic approach proved efficient in identifying and showcasing research focal points and budding trends using network charts within the DDPP framework.
resultsOur findings indicate that: in countries, institutes, years, authors, and journals, the dominant entities were the United States, the University of Bonn in Germany, the year 2021, Dr Jae Hui Kim from South Korea, and the journal "Retina"; in accordance with the TMSD, AMD research trends have not changed significantly since 2014, as the top 4 categories for 3 citing, active, and cited articles have not changed, in sequence (Ophthalmology, Science & Technology - Other Topics, General & Internal Medicine, Pharmacology & Pharmacy).
conclusionThe introduced TMSD, which incorporates the FLCA algorithm and features in 3 columns-cited, active, and citing research categories-offers readers clearer insights into research developments compared to the traditional dual-map overlays from CiteSpace software. Such tools are especially valuable for streamlining the visualization of the intricate data often seen in bibliometric studies.
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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.