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Large Language Models in Ophthalmology: A Bibliographic Analysis.

Neslihan Dilruba Köseoğlu1, T Y Alvin Liu2

  • 1Tufts Medical Center, Clinic of Ophthalmology, Boston, MA, USA.

Turkish Journal of Ophthalmology
|April 27, 2026
PubMed
Summary
This summary is machine-generated.

Research on large language models (LLMs) in ophthalmology is concentrated in clinical decision-making, particularly for retinal conditions. The study highlights significant gender and geographic disparities in LLM research authorship.

Keywords:
Large language modelsbibliographical analysisophthalmology

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Bibliometrics

Background:

  • Large language models (LLMs) are increasingly explored for applications in various medical fields.
  • Ophthalmology presents unique opportunities for LLM integration in clinical practice, education, and patient engagement.
  • Understanding the current research landscape is crucial for identifying trends and gaps.

Purpose of the Study:

  • To conduct a comprehensive bibliographic analysis of research on large language models (LLMs) in ophthalmology.
  • To map the distribution of LLM research across different ophthalmic subspecialties and application areas.
  • To examine geographical representation and author characteristics, including gender and scholarly impact.

Main Methods:

  • Bibliographic analysis of articles indexed in PubMed up to November 2024.
  • Categorization of studies into clinical decision-making, education, patient interactions, and miscellaneous applications.
  • Descriptive statistical analysis of study distribution by subspecialty, region, journal quality, and author demographics (gender, h-index, i10-index).

Main Results:

  • Clinical decision-making was the predominant application area (43.7%), with a focus on retinal studies (39.5%).
  • North America (48.3%) led in research output, followed by Asia (29.9%) and Europe (20.7%).
  • A significant gender disparity was observed, with female authors comprising less than 30% of first, last, and corresponding authors.

Conclusions:

  • LLM research in ophthalmology is rapidly growing, with a strong emphasis on clinical decision support, especially for retinal diseases.
  • Current research exhibits geographical concentration and notable gender imbalances in authorship.
  • Promoting diversity in gender and geographic representation is essential for equitable advancement in ophthalmology LLM research.