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Analysis of international publication trends in artificial intelligence in ophthalmology

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Abstract

Purpose

Artificial intelligence (AI) has entered the field of medicine, and ophthalmology is no exception. The objective of this study was to report on scientific production and publication trends, to identify journals, countries, international collaborations, and major MeSH terms involved in AI in ophthalmology research.

Methods

Scientometric methods were used to evaluate global scientific production and development trends in AI in ophthalmology using PubMed and the Web of Science Core Collection.

Results

A total of 1356 articles were retrieved over the period 1966–2019. The yearly growth of AI in ophthalmology publications has been 18.89% over the last ten years, indicating that AI in ophthalmology is a very attractive topic in science. Analysis of the most productive journals showed that most were specialized in computer and medical systems. No journal was found to specialize in AI in ophthalmology. The USA, China, and the UK were the three most productive countries. The study of international collaboration showed that, besides the USA, researchers tended to collaborate with peers from neighboring countries. Among the twenty most frequent MeSH terms retrieved, there were only four related to clinical topics, revealing the retina and glaucoma as the most frequently encountered subjects of interest in AI in ophthalmology. Analysis of the top ten Journal Citation Reports categories of journals and MeSH terms for articles confirmed that AI in ophthalmology research is mainly focused on engineering and computing and is mainly technical research related to computer methods.

Conclusions

This study provides a broad view of the current status and trends in AI in ophthalmology research and shows that AI in ophthalmology research is an attractive topic focusing on retinal diseases and glaucoma. This study may be useful for researchers in AI in ophthalmology such as clinicians, but also for scientists to better understand this research topic, know the main actors in this field (including journals and countries), and have a general overview of this research theme.

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Author information

Authors and Affiliations

  1. Normandie Univ, UNICAEN, Média Normandie, Caen, France

    Christophe Boudry

  2. URFIST, Ecole Nationale des Chartes, PSL Research University, Paris, France

    Christophe Boudry

  3. LaTIM, UMR 1101 INSERM, Université de Bretagne Occidentale, Brest, France

    Hassan Al Hajj

  4. Service d’Ophtalmologie, CHU Dijon, Dijon, France

    Louis Arnould

  5. INSERM, Univ Rennes, CHU Rennes, Department of Ophthalmology, CLCC Eugène Marquis, COSS [(Chemistry Oncogenesis Stress Signaling)] – UMR_S 1242, 35000, Rennes, France

    Frederic Mouriaux

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  1. Christophe Boudry
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  2. Hassan Al Hajj
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  3. Louis Arnould
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  4. Frederic Mouriaux
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Contributions

Christophe Boudry and Frederic Mouriaux designed the work; Christophe Boudry acquired data; Christophe Boudry, Hassan Al Hajj, Louis Arnould, and Frederic Mouriaux undertook analyses; Christophe Boudry, Hassan Al Hajj, Louis Arnould, and Frederic Mouriaux drafted the work and contributed to its revision and have approved the submitted version.

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Correspondence to Christophe Boudry.

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Boudry, C., Al Hajj, H., Arnould, L. et al. Analysis of international publication trends in artificial intelligence in ophthalmology. Graefes Arch Clin Exp Ophthalmol 260, 1779–1788 (2022). https://doi.org/10.1007/s00417-021-05511-7

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  • DOI: https://doi.org/10.1007/s00417-021-05511-7

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