{"title":"Artificial intelligence and perinatology: a study on accelerated academic production- a bibliometric analysis.","authors":"Ümran Kılınçdemir Turgut","doi":"10.3389/fmed.2025.1505450","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Materials and methods: </strong>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.\"</p><p><strong>Results: </strong>In this bibliometric study, it was found that the most frequently published journal among the 382 examined articles was <i>Medical Image Analysis</i>, while the journals with the most publications in the field of perinatology were <i>Prenatal Diagnosis</i> and <i>Ultrasound in Obstetrıcs & Gynecology.</i> 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).</p><p><strong>Conclusion: </strong>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 the AI era in perinatology. Milestones are being laid on the path from prenatal screening to prenatal treatment.</p>","PeriodicalId":12488,"journal":{"name":"Frontiers in Medicine","volume":"12 ","pages":"1505450"},"PeriodicalIF":3.1000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11883689/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fmed.2025.1505450","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: 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.
Materials and methods: 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).
Conclusion: 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 the AI era in perinatology. Milestones are being laid on the path from prenatal screening to prenatal treatment.
期刊介绍:
Frontiers in Medicine publishes rigorously peer-reviewed research linking basic research to clinical practice and patient care, as well as translating scientific advances into new therapies and diagnostic tools. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
In addition to papers that provide a link between basic research and clinical practice, a particular emphasis is given to studies that are directly relevant to patient care. In this spirit, the journal publishes the latest research results and medical knowledge that facilitate the translation of scientific advances into new therapies or diagnostic tools. The full listing of the Specialty Sections represented by Frontiers in Medicine is as listed below. As well as the established medical disciplines, Frontiers in Medicine is launching new sections that together will facilitate
- the use of patient-reported outcomes under real world conditions
- the exploitation of big data and the use of novel information and communication tools in the assessment of new medicines
- the scientific bases for guidelines and decisions from regulatory authorities
- access to medicinal products and medical devices worldwide
- addressing the grand health challenges around the world