Evidence map›Paper›PMID 37222839›Full record

ArticleArchives of gynecology and obstetrics2023

Exploring the use of ChatGPT in OBGYN: a bibliometric analysis of the first ChatGPT-related publications.

Gabriel Levin, Yoav Brezinov, Raanan Meyer

Abstract read
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In one paragraph

Article in Archives of gynecology and obstetrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Can ChatGPT Provide Patient-Friendly and Reliable Information on Cervical Cancer Screening? A Study of ChatGPT-Generated Information in Polish.Medical science monitor : international medical journal of experimental and clinical research · 2025
    Article
  6. ChatGPT in Academic Writing: A Scientometric Analysis of Literature Published Between 2022 and 2023.Journal of empirical research on human research ethics : JERHRE · 2025
    Article
  7. Article
  8. Article
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  10. Article
  11. Bibliometric analysis of ChatGPT in medicine.International journal of emergency medicine · 2024
    Article
  12. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Gabriel LevinThe Department of Gynecologic Oncology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel. levin.gaby@gmail.com.ORCID http://orcid.org/0000-0003-1282-5379
Yoav BrezinovExperimental Surgery, McGill University, Quebec, Canada.
Raanan MeyerDivision of Minimally Invasive Gynecologic Surgery, Department of Obstetrics and Gynecology, Cedars Sinai Medical Center, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeLittle is known about the scientific literature regarding the new revolutionary tool, ChatGPT. We aim to perform a bibliometric analysis to identify ChatGPT-related publications in obstetrics and gynecology (OBGYN). STUDY

designA bibliometric study through PubMed database. We mined all ChatGPT-related publications using the search term "ChatGPT". Bibliometric data were obtained from the iCite database. We performed a descriptive analysis. We further compared IF among publications describing a study vs. other publications.

resultsOverall, 42 ChatGPT-related publications were published across 26 different journals during 69 days. Most publications were editorials (52%) and news/briefing (22%), with only one (2%) research article identified. Five (12%) publications described a study performed. No ChatGPT-related publications in OBGYN were found. The leading journal by the number of publications was Nature (24%), followed by Lancet Digital Health and Radiology (7%, for both). The main subjects of publications were ChatGPT's scientific writing quality (26%) and a description of ChatGPT (26%) followed by tested performance of ChatGPT (14%), authorship and ethical issues (10% for both topics).In a comparison of publications describing a study performed (n = 5) vs. other publications (n = 37), mean IF was lower in the study-publications (mean 6.25 ± 0 vs. 25.4 ± 21.6, p < .001).

conclusionsThe study highlights main trends in ChatGPT-related publications. OBGYN is yet to be represented in this literature.

Indexed as

GynecologyObstetricsArtificial IntelligenceBibliometricsDatabases, FactualHumansPublicationsArtificial intelligenceBibliometricsChatGPTOBGYN literatureResearch

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.