Advancing ophthalmology with large language models: Applications, challenges, and future directions.

Abstract

In recent years, with the rapid development of artificial intelligence (AI) technology, large language models (LLMs), as powerful tools, are expected to transform traditional medical practices and improve medical efficiency and quality. In the field of ophthalmology, LLMs not only assist doctors in diagnosing eye diseases, optimizing treatment recommendations, improving medical record-writing efficiency, and providing educational training support, but also offer strong support for ophthalmic researchers in data processing and innovative research. LLMs, however, face numerous challenges in clinical applications, such as knowledge boundaries, AI hallucinations, and data privacy protection. We summarize the progress of LLM applications in the field of ophthalmology and highlight the challenges, providing references for their future use in clinical practice.