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Updated: Jun 6, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Large Language Model Authorship in Ophthalmic Publications.

Christopher R Fortenbach1, Yue S Wu2, Parth M Mungra3

  • 1Department of Ophthalmology, University of Washington School of Medicine, Seattle, WA, USA; Karalis-Johnson Retina Center, Department of Ophthalmology, University of Washington School of Medicine, Seattle, WA, USA.

Ophthalmology
|June 4, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI)-generated text is increasingly found in ophthalmology research, with 25.7% of articles showing AI likelihood by 2025. This AI use is rarely disclosed, posing risks to scientific integrity.

Keywords:
AI detectionChatGPTLarge language modelsartificial intelligenceophthalmology

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Area of Science:

  • Ophthalmology
  • Medical Research
  • Artificial Intelligence

Background:

  • The rapid advancement of artificial intelligence (AI) presents new tools for scientific writing.
  • The potential for AI-generated text in scholarly publications necessitates evaluation.

Purpose of the Study:

  • To assess the prevalence of AI-generated text in the ophthalmology literature.
  • To evaluate the disclosure practices of AI use in published research.

Main Methods:

  • Analysis of 27,142 ophthalmology research articles published between May 2020 and May 2025.
  • Validation of four AI-detection services, with GPTZero selected for large-scale screening.
  • Evaluation of word-frequency changes and stylistic indicators associated with Large Language Models (LLMs).

Main Results:

  • A significant increase in AI-likelihood scores was observed post-ChatGPT release across research and commentary articles.
  • By 2025, 25.7% of research articles and 21.6% of commentary articles exhibited high AI-likelihood scores.
  • AI-generated text was detected in 22.3% of sentences in research articles and 90% in commentary articles, with no disclosure.

Conclusions:

  • Large Language Model (LLM)-generated text is increasingly prevalent in the ophthalmic literature.
  • Undisclosed AI use poses a significant risk to authorship integrity and the reliability of published findings.
  • There is a critical need for disclosure requirements and editorial oversight to manage AI integration in scientific publishing.