SynthesisFrontiers in medicine2025
Artificial intelligence in dysphagia since the 21st century: a bibliometric and visualization study.
Synthesis in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Artificial intelligence tools for the assessment and management of dysphagia: a scoping review.BMJ open · 2026Article
- Review
- Artificial intelligence for surgical management of benign esophageal disease: scoping review and evidence mapping.Langenbeck's archives of surgery · 2026Article
- Application of intelligent technologies for dysphagia risk prediction: A scoping review.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The fields of dysphagia is progressively acknowledging the transformative capacity of artificial intelligence (AI). The implementation of this technology is profoundly impacting research directions, clinical practices, and healthcare systems. However, existing studies remain scattered and predominantly focus on specific techniques or case applications, lacking a systematic synthesis of global research output, influential contributors, collaboration networks, and evolving thematic trends. A comprehensive bibliometric review is therefore essential to map the current landscape and guide future interdisciplinary research. Methods: This study applies bibliometric and visual analysis methods to comprehensively review the global research activities in AI in dysphagia. Data from 633 articles published by 3,533 authors in 292 journals from January 2000 to February 2025 in Web of Science Core Collection (WoSCC) database were collected and analyzed to identify top publications, sources, authors, institutions, countries/regions, and keywords. Results: The research activity of AI in dysphagia, which shows an overall upward trend that can be divided into three distinct periods: the first phase (2000-2012), the second phase (2013-2017) and the third phase (2018-Present). The most cited article was Radiotherapy vs. transoral robotic surgery and neck dissection for oropharyngeal squamous cell carcinoma (ORATOR): an open-label, phase 2, randomized trial (344 citations). The most prolific journal was Head and Neck-Journal for the Sciences and Specialties of the Head and Neck with 30 publications. Sejdic Ervin (28 articles), the University of Pittsburgh (39 articles), and the USA (255 articles) were the leading author, institution, and country, respectively. Dysphagia was the most frequently occurring keyword (286 occurrences), while emerging terms included machine learning (ML) and deep learning (DL). Conclusion: This bibliometric analysis reveals the evolving landscape of AI research in dysphagia, highlighting current hotspots and future directions. AI is driving significant shifts in both research and clinical practice in dysphagia; however, challenges such as interdisciplinary integration and ethical considerations remain to be addressed.
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.