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Topic Collection

Generative AI in Ophthalmology

The field of ophthalmology has witnessed remarkable advancements in recent years, and the emergence of generative artificial intelligence (AI) techniques has further revolutionized research and clinical applications. This topic collection aims to explore the latest developments, challenges, and opportunities in the application of generative AI methods specifically tailored to ophthalmology. Scope and topics: British Journal of Ophthalmology invites researchers and practitioners from academia and industry to contribute their original research, reviews, or perspectives on various aspects of generative AI in ophthalmology. The topics of interest for this topic collection include, but are not limited to:
  • Generative models for retinal image analysis and interpretation
  • Synthetic data generation for ophthalmic imaging and diagnostics
  • Deep learning approaches for ophthalmic image generation and augmentation
  • Adversarial learning and generative adversarial networks (GANs) in ophthalmology
  • Transfer learning and domain adaptation in generative AI for ophthalmology
  • Explainability and interpretability of generative AI models in ophthalmic applications
  • Clinical applications of generative AI in ophthalmology, such as disease diagnosis, prognosis, treatment planning and interactive question and answering
  • Ethical considerations and challenges in the use of generative AI in ophthalmology
All submissions will undergo a rigorous peer-review process, and accepted papers will be published in the themed issue of British Journal of Ophthalmology. Submissions are now closed. For any inquiries regarding this topic collection, please contact the Guest Editors at bjo@bmj.com. We look forward to receiving your contributions and making this topic collection a comprehensive resource for the exploration and advancement of generative AI in ophthalmology.

Published Articles

Capabilities of GPT-4 in ophthalmology: an analysis of model entropy and progress towards human-level medical question answering (3 November 2023) Fares Antaki, Daniel Milad, Mark A Chia, Charles-Édouard Giguère, Samir Touma, Jonathan El-Khoury, Pearse A Keane, Renaud Duval Performance of ChatGPT and Bard on the official part 1 FRCOphth practice questions (6 November 2023) Thomas Fowler, Simon Pullen, Liam Birkett Review of emerging trends and projection of future developments in large language models research in ophthalmology (11 December 2023) Matthew Wong, Zhi Wei Lim, Krithi Pushpanathan, Carol Y Cheung, Ya Xing Wang, David Chen, Yih Chung Tham Deep learning model for extensive smartphone-based diagnosis and triage of cataracts and multiple corneal diseases (19 January 2024) Yuta Ueno, Masahiro Oda, Takefumi Yamaguchi, Hideki Fukuoka, Ryohei Nejima, Yoshiyuki Kitaguchi, Masahiro Miyake, Masato Akiyama, Kazunori Miyata, Kenji Kashiwagi, Naoyuki Maeda, Jun Shimazaki, Hisashi Noma, Kensaku Mori, Tetsuro Oshika Assessing the medical reasoning skills of GPT-4 in complex ophthalmology cases (16 February 2024) Daniel Milad, Fares Antaki, Jason Milad, Andrew Farah, Thomas Khairy, David Mikhail, Charles-Édouard Giguère, Samir Touma, Allison Bernstein, Andrei-Alexandru Szigiato, Taylor Nayman, Guillaume A Mullie, Renaud Duval Exploring AI-chatbots’ capability to suggest surgical planning in ophthalmology: ChatGPT versus Google Gemini analysis of retinal detachment cases (6 March 2024) Matteo Mario Carlà, Gloria Gambini, Antonio Baldascino, Federico Giannuzzi, Francesco Boselli, Emanuele Crincoli, Nicola Claudio D’Onofrio, Stanislao Rizzo Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images (14 March 2024) Hitoshi Tabuchi, Justin Engelmann, Fumiatsu Maeda, Ryo Nishikawa, Toshihiko Nagasawa, Tomofusa Yamauchi, Mao Tanabe, Masahiro Akada, Keita Kihara, Yasuyuki Nakae, Yoshiaki Kiuchi, Miguel O Bernabeu Validation of a deep learning model for automatic detection and quantification of five OCT critical retinal features associated with neovascular age-related macular degeneration (14 March 2024) Federico Ricardi, Jonathan Oakley, Daniel Russakoff, Giacomo Boscia, Paolo Caselgrandi, Francesco Gelormini, Andrea Ghilardi, Giulia Pintore, Tommaso Tibaldi, Paola Marolo, Francesco Bandello, Michele Reibaldi, Enrico Borrelli ICGA-GPT: report generation and question answering for indocyanine green angiography images (20 March 2024) Xiaolan Chen, Weiyi Zhang, Ziwei Zhao, Pusheng Xu, Yingfeng Zheng, Danli Shi, Mingguang He Creating realistic anterior segment optical coherence tomography images using generative adversarial networks (2 May 2024) Jad F Assaf, Anthony Abou Mrad, Dan Z Reinstein, Guillermo Amescua, Cyril Zakka, Timothy J Archer, Jeffrey Yammine, Elsa Lamah, Michèle Haykal, Shady T Awwad Medical education with large language models in ophthalmology: custom instructions and enhanced retrieval capabilities (7 May 2024) Mertcan Sevgi, Fares Antaki, Pearse A Keane

Guest Editors

Mingguang He The Hong Kong Polytechnic University Hong Kong, SAR of China ORCID id logoorcid.org/0000-0002-6912-2810
Pearse Keane Moorfields Eye Hospital London, UK ORCID id logoorcid.org/0000-0002-9239-745X
Aaron Lee University of Washington Seattle, USA ORCID id logoorcid.org/0000-0002-7452-1648