Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107461
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dc.contributorSchool of Optometryen_US
dc.creatorBetzler, BKen_US
dc.creatorChen, Hen_US
dc.creatorCheng, CYen_US
dc.creatorLee, CSen_US
dc.creatorNing, Gen_US
dc.creatorSong, SJen_US
dc.creatorLee, AYen_US
dc.creatorKawasaki, Ren_US
dc.creatorvan, Wijngaarden, Pen_US
dc.creatorGrzybowski, Aen_US
dc.creatorHe, Men_US
dc.creatorLi, Den_US
dc.creatorRan, Ran, Aen_US
dc.creatorTing, DSWen_US
dc.creatorTeo, Ken_US
dc.creatorRuamviboonsuk, Pen_US
dc.creatorSivaprasad, Sen_US
dc.creatorChaudhary, Ven_US
dc.creatorTadayoni, Ren_US
dc.creatorWang, Xen_US
dc.creatorCheung, CYen_US
dc.creatorZheng, Yen_US
dc.creatorWang, YXen_US
dc.creatorTham, YCen_US
dc.creatorWong, TYen_US
dc.date.accessioned2024-06-25T04:31:07Z-
dc.date.available2024-06-25T04:31:07Z-
dc.identifier.urihttp://hdl.handle.net/10397/107461-
dc.language.isoenen_US
dc.publisherThe Lancet Publishing Groupen_US
dc.rightsCopyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Betzler, B. K., Chen, H., Cheng, C.-Y., Lee, C. S., Ning, G., Song, S. J., Lee, A. Y., Kawasaki, R., van Wijngaarden, P., Grzybowski, A., He, M., Li, D., Ran Ran, A., Ting, D. S. W., Teo, K., Ruamviboonsuk, P., Sivaprasad, S., Chaudhary, V., Tadayoni, R., . . . Wong, T. Y. (2023). Large language models and their impact in ophthalmology. The Lancet Digital Health, 5(12), e917-e924 is available at https://doi.org/10.1016/S2589-7500(23)00201-7.en_US
dc.titleLarge language models and their impact in ophthalmologyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spagee917en_US
dc.identifier.epagee924en_US
dc.identifier.volume5en_US
dc.identifier.issue12en_US
dc.identifier.doi10.1016/S2589-7500(23)00201-7en_US
dcterms.abstractThe advent of generative artificial intelligence and large language models has ushered in transformative applications within medicine. Specifically in ophthalmology, large language models offer unique opportunities to revolutionise digital eye care, address clinical workflow inefficiencies, and enhance patient experiences across diverse global eye care landscapes. Yet alongside these prospects lie tangible and ethical challenges, encompassing data privacy, security, and the intricacies of embedding large language models into clinical routines. This Viewpoint highlights the promising applications of large language models in ophthalmology, while weighing up the practical and ethical barriers towards their real-world implementation. This Viewpoint seeks to stimulate broader discourse on the potential of large language models in ophthalmology and to galvanise both clinicians and researchers into tackling the prevailing challenges and optimising the benefits of large language models while curtailing the associated risks.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationThe lancet digital health, Dec. 2023, v. 5, no. 12, p. e917-e924en_US
dcterms.isPartOfThe lancet digital healthen_US
dcterms.issued2023-12-
dc.identifier.scopus2-s2.0-85177769213-
dc.identifier.eissn2589-7500en_US
dc.description.validate202406 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2877a-
dc.identifier.SubFormID48617-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Medical Research Council of Singapore ; National Key R&D Program, Chinaen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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