ArticleTranslational pediatrics2026
Artificial intelligence in pediatrics: a bibliometric analysis of global output, networks, and frontiers [2016-2025].
Article in Translational pediatrics, 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Although artificial intelligence (AI) is increasingly used to prevent, diagnose, and treat pediatric diseases, a quantitative panorama of the global research landscape is lacking. This study aimed to map the evolution of AI-focused pediatric literature, identify leading actors and themes, and detect emerging directions over the past decade. Methods: Publications from 2016 to 2025 were retrieved from the Web of Science Core Collection (WoSCC) and analyzed with CiteSpace 6.4 R1 for volume trends, citation impact, collaboration networks (country/institution), keyword co-occurrence, burst detection, and co-citation clusters. Results: Of 1,893 articles, annual output rose from 53 to 526 (R Conclusions: AI applications in pediatrics are expanding rapidly, but collaboration remains institutionally fragmented. Connectivity, rather than mere productivity, underpins global influence; future efforts should adopt domain-specific strategies: prospective validation for mature imaging domains, data standardization for inconsistent areas, and ethical frameworks for emerging technologies, to accelerate safe clinical translation.
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.