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Generative artificial intelligence in ophthalmology.
Waisberg, Ethan; Ong, Joshua; Kamran, Sharif Amit; Masalkhi, Mouayad; Paladugu, Phani; Zaman, Nasif; Lee, Andrew G; Tavakkoli, Alireza.
Afiliação
  • Waisberg E; Department of Ophthalmology, University of Cambridge, Cambridge, United Kingdom. Electronic address: ew690@cam.ac.uk.
  • Ong J; Michigan Medicine, University of Michigan, Ann Arbor, United States.
  • Kamran SA; School of Medicine, University College Dublin, Belfield, Dublin, Ireland.
  • Masalkhi M; School of Medicine, University College Dublin, Belfield, Dublin, Ireland.
  • Paladugu P; Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, United States; Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.
  • Zaman N; Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, Nevada, United States.
  • Lee AG; Center for Space Medicine, Baylor College of Medicine, Houston, Texas, United States; Department of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, Houston, Texas, United States; The Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, United States; De
  • Tavakkoli A; Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, Nevada, United States.
Surv Ophthalmol ; 2024 May 16.
Article em En | MEDLINE | ID: mdl-38762072
ABSTRACT
Generative AI has revolutionized medicine over the past several years. A generative adversarial network (GAN) is a deep learning framework that has become a powerful technique in medicine, particularly in ophthalmology and image analysis. In this paper we review the current ophthalmic literature involving GANs, and highlight key contributions in the field. We briefly touch on ChatGPT, another application of generative AI, and its potential in ophthalmology. We also explore the potential uses for GANs in ocular imaging, with a specific emphasis on 3 primary domains image enhancement, disease identification, and generating of synthetic data. PubMed, Ovid MEDLINE, Google Scholar were searched from inception to October 30, 2022 to identify applications of GAN in ophthalmology. A total of 40 papers were included in this review. We cover various applications of GANs in ophthalmic-related imaging including optical coherence tomography, orbital magnetic resonance imaging, fundus photography, and ultrasound; however, we also highlight several challenges, that resulted in the generation of inaccurate and atypical results during certain iterations. Finally, we examine future directions and considerations for generative AI in ophthalmology.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article