ReviewJournal of robotic surgery2025
Research trends of global artificial intelligence application in obstetrics and gynecology from 1999 to 2025: a bibliometric analysis based on web of science.
Review in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Suggestions and insights from 28 bibliometric studies in the Journal of Robotic Surgery.Journal of robotic surgery · 2025Pooled it
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
Artificial intelligence (AI) has rapidly advanced in the medical field, with a notable increase in its applications within obstetrics and gynecology. This study aims to identify key research trends in AI applications in this domain over recent Years through bibliometric analysis and to predict future research directions. Following a comprehensive analysis and screening, 926 articles were selected for inclusion in this study. The overall publication output exhibited a consistent upward trend, suggesting significant potential for future research advancements. Among individual contributors, the most prolific authors were Laios, Alexandros (11 publications), Kalampokis, Evangelos (10 publications), and Nugent, David (9 publications). The leading institutions, ranked by publication volume, were all based in the United States: the University of California System (28 publications), Harvard University (22 publications), and the University of Texas System (21 publications). At the countries/regions level, the top three countries/regions by research output were the People's Republic of China (283 publications), the United States (228 publications), and the United Kingdom (78 publications), all of which demonstrated strong international collaboration networks. These publications spanned 81 research domains, with obstetrics & gynecology being the most frequently addressed field (307 publications). In terms of keyword frequency, the five most prevalent keywords were "machine learning" (184 occurrences), "risk" (108 occurrences), "women" (105 occurrences), "artificial intelligence" (103 occurrences), and "labor" (89 occurrences). Keyword clustering analysis revealed ten distinct thematic clusters, primarily centered around three key areas: auxiliary diagnosis and treatment, health management, and robotic surgery in obstetrics and gynecology. The keyword with the highest burst intensity was "pregnancy," while recently emerged and sustained high-intensity keywords included "resistance," "induction," "classification," and "prediction." AI technology in obstetrics and gynecology is advancing rapidly. To stimulate breakthroughs and foster innovation, enhanced collaboration among researchers and institutions is essential. Looking forward, the integration of AI with obstetrics and gynecology is poised to offer substantial benefits and is anticipated to become a pivotal trend and area of focus in the field's future advancement.
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.