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Editorial
Embracing generative AI in ophthalmology
  1. Frank Larkin1,
  2. Mingguang He2
  1. 1 NIHR Moorfields Biomedical Research Centre, London, UK
  2. 2 The Hong Kong Polytechnic University, Hong Kong, China
  1. Correspondence to Dr Mingguang He; mingguang_he{at}yahoo.com

https://doi.org/10.1136/bjo-2024-326320

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    Ophthalmology has been at the forefront of research on artificial intelligence (AI) in medicine. To some extent, this is due to the transparency of eye structures and the feasibility of detailed imaging, which lends itself to data extraction and high-quality databanks of digital images. Nor is that all: another reason for the pre-eminence of ophthalmology in AI research is the potential use of data taken from eye images and measurements to predict and detect diseases which are not eye-specific such as heart failure, ischaemic stroke and Parkinson’s disease.1 At a time when the BJO is receiving manuscripts on AI at a rate of at least 15 per month, we decided to showcase the ophthalmic research activity in generative AI in particular, with a call in late 2023 for manuscripts for a Special Topic edition on Generative AI in Ophthalmology. We are grateful to guest editors Pearse Keane (Moorfields Eye Hospital & University College London, UK) and Aaron Lee (University of Washington, Seattle, Washington, USA) for their contributions to this BJO …

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    Footnotes

    • X @mingguanghe

    • Contributors FL and MH contributed to the drafting of manuscript. FL and MH contributed to the review and revision of manuscript.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; internally peer reviewed.