Prashant D Tailor, Haley S D'Souza, Hanzhou Li, Matthew R Starr
{"title":"Vision of the future: large language models in ophthalmology.","authors":"Prashant D Tailor, Haley S D'Souza, Hanzhou Li, Matthew R Starr","doi":"10.1097/ICU.0000000000001062","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>Large language models (LLMs) are rapidly entering the landscape of medicine in areas from patient interaction to clinical decision-making. This review discusses the evolving role of LLMs in ophthalmology, focusing on their current applications and future potential in enhancing ophthalmic care.</p><p><strong>Recent findings: </strong>LLMs in ophthalmology have demonstrated potential in improving patient communication and aiding preliminary diagnostics because of their ability to process complex language and generate human-like domain-specific interactions. However, some studies have shown potential for harm and there have been no prospective real-world studies evaluating the safety and efficacy of LLMs in practice.</p><p><strong>Summary: </strong>While current applications are largely theoretical and require rigorous safety testing before implementation, LLMs exhibit promise in augmenting patient care quality and efficiency. Challenges such as data privacy and user acceptance must be overcome before LLMs can be fully integrated into clinical practice.</p>","PeriodicalId":50604,"journal":{"name":"Current Opinion in Ophthalmology","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Ophthalmology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/ICU.0000000000001062","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/30 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose of review: Large language models (LLMs) are rapidly entering the landscape of medicine in areas from patient interaction to clinical decision-making. This review discusses the evolving role of LLMs in ophthalmology, focusing on their current applications and future potential in enhancing ophthalmic care.
Recent findings: LLMs in ophthalmology have demonstrated potential in improving patient communication and aiding preliminary diagnostics because of their ability to process complex language and generate human-like domain-specific interactions. However, some studies have shown potential for harm and there have been no prospective real-world studies evaluating the safety and efficacy of LLMs in practice.
Summary: While current applications are largely theoretical and require rigorous safety testing before implementation, LLMs exhibit promise in augmenting patient care quality and efficiency. Challenges such as data privacy and user acceptance must be overcome before LLMs can be fully integrated into clinical practice.
期刊介绍:
Current Opinion in Ophthalmology is an indispensable resource featuring key up-to-date and important advances in the field from around the world. With renowned guest editors for each section, every bimonthly issue of Current Opinion in Ophthalmology delivers a fresh insight into topics such as glaucoma, refractive surgery and corneal and external disorders. With ten sections in total, the journal provides a convenient and thorough review of the field and will be of interest to researchers, clinicians and other healthcare professionals alike.