Utilizing Large Language Models in Ophthalmology: The Current Landscape and Challenges

Peranut Chotcomwongse ¹, Paisan Ruamviboonsuk ¹, Andrzej Grzybowski ^2,3

⁰Vitreoretina Unit, Department of Ophthalmology, Rajavithi Hospital, Rungsit University, Bangkok, Thailand.

Ophthalmology and Therapy +

|

August 24, 2024

View abstract on PubMed

Summary

Large language models (LLMs) offer advanced AI capabilities for understanding and generating text. This review explores their growing role and potential applications in the field of ophthalmology and eye care.

Area Of Science

Artificial Intelligence
Natural Language Processing
Ophthalmology

Background

Large language models (LLMs) are AI systems adept at processing and generating human-like text.
Their interactive capabilities enhance user experiences in human-AI communication.
LLMs can synthesize information from diverse sources to address various queries.

Purpose Of The Study

To review the performance of LLMs in ophthalmology.
To explore the potential applications of LLMs in eye care.
To summarize current literature on LLMs in the medical field of ophthalmology.

Main Methods

Literature review of current publications.
Analysis of LLM capabilities in text understanding and generation.
Assessment of LLM integration with other technologies in ophthalmology.

Main Results

LLMs demonstrate significant potential in understanding and generating human-like language.
Their application in ophthalmology is emerging, driven by the field's technological integration.
LLMs can support tasks like problem-solving and information synthesis relevant to eye care.

Conclusions

LLMs are poised to become integral tools in ophthalmology.
Their capabilities align with the increasing use of AI and telemedicine in eye care.
Further research and development are expected to expand LLM utility in this medical domain.

Keywords:

Artificial intelligence Bard ChatGPT Copilot Large language model Ophthalmology Telemedicine