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Ethical considerations for large language models in ophthalmology.

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Large language models (LLMs) offer benefits in ophthalmology for education and clinical support. However, ethical issues like data privacy and accuracy risks necessitate careful integration with human oversight.

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Ethics

Background:

  • Large language models (LLMs) are increasingly explored for applications in healthcare.
  • Ophthalmology presents unique opportunities and challenges for LLM integration.

Purpose of the Study:

  • To review and discuss the ethical considerations of using large language models (LLMs) in ophthalmology.
  • To summarize the current landscape of LLM applications and associated ethical challenges in the field.

Main Methods:

  • Systematic review of 47 articles on LLM applications in ophthalmology.
  • Analysis of identified ethical concerns, including data interpretation, recommendation accuracy, and privacy.

Main Results:

  • LLMs show potential in ophthalmology for education, research, clinical decision support, and surgical note assistance.
  • Key ethical concerns include inaccurate data interpretation, risk of harmful recommendations, and data privacy breaches.
  • Human oversight, transparency, and accountability are crucial for safe AI integration.

Conclusions:

  • LLM integration in ophthalmology can enhance clinical decision support and medical education.
  • Ethical challenges encompass data privacy, misinformation, and dataset biases.
  • Responsible adoption requires addressing these concerns and promoting careful user practices.