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SYSTEMATIC REVIEW article

Front. Med.
Sec. Obstetrics and Gynecology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1505450

Artificial Intelligence and Perinatology: A Study on Accelerated Academic Production-A Bibliometric Analysis Running head: Artificial Intelligence in Perinatology

Provisionally accepted
  • Adana City Training and Research Hospital, Ministry of Health (Turkey), Adana, Türkiye

The final, formatted version of the article will be published soon.

    The main purpose of this bibliometric study is to compile the rapidly increasing articles in the field of perinatology in recent years and to shed light on the research areas where studies are concentrated.: This bibliometric study was conducted using the Thomson ISI Web of Science Core Collection (WOSCC) system on May 4, 2024, with specific keywords. The abstracts of 1,124 articles that met the criteria were reviewed, and 382 articles related to perinatology were evaluated. Keyword co-occurrence, co-citation of authors, and co-citation of references analyses were conducted using VOSviewer (version 1.6.19). Out of these, 121 articles with 10 or more citations were analyzed in terms of their content and categorized under the headings 'Purpose of Evaluation,' 'Medical Methods and Parameters Used,' 'Output To Be Evaluated,' and 'Fetal System or Region Being Evaluated.' Results: In this bibliometric study, it was found that the most frequently published journal among the 382 examined articles was Medical Image Analysis, while the journals with the most publications in the field of perinatology were Prenatal Diagnosis and Ultrasound in Obstetrıcs & Gynecology. The most commonly used keyword was "deep learning."(115/382).Among the 121 highly cited articles, the most common purpose of evaluation was "Prenatal Screening." Artificial intelligence was most frequently used in ultrasound (59.8%) imaging, with MRI (20.5%) in second place. Among the evaluated outputs, 'organ scanning' (35/121) was in first place, while 'biometry' (34/121) was in second place. In terms of evaluated systems and organs, "growth screening"(35/121) was the most common, followed by the "neurological system"(33/121) and then the "cardiovascular system"(18/121).I has witnessed the increasing influence of artificial intelligence in the field of perinatology in recent years. This impact may mark the historic beginning of the transition to 3 the AI era in perinatology. Milestones are being laid on the path from prenatal screening to prenatal treatment.

    Keywords: deep learning, machine learning, artificial intelligence, Perinatology, bibliometric analysis, fetal imaging techniques

    Received: 02 Oct 2024; Accepted: 22 Jan 2025.

    Copyright: © 2025 Kılınçdemir Turgut. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ümran Kılınçdemir Turgut, Adana City Training and Research Hospital, Ministry of Health (Turkey), Adana, Türkiye

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.