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New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology
  1. Siddharth Nath1,2,
  2. Abdullah Marie3,
  3. Simon Ellershaw4,
  4. Edward Korot5,
  5. Pearse A Keane2
  1. 1Ophthalmology and Visual Sciences, McGill University, Montreal, Quebec, Canada
  2. 2National Institute for Health Research, Biomedical Research Centre for Ophthalmology, UCL Institute of Ophthalmology, Moorfields Eye Hospital City Road Campus, London, UK
  3. 3School of Medicine and Dentistry, Queen's University Belfast, Belfast, UK
  4. 4UKRI Centre for Doctoral Training in AI-enabled Healthcare, University College London, London, UK
  5. 5Byers Eye Institute, Stanford University, Stanford, California, USA
  1. Correspondence to Dr Pearse A Keane, National Institute for Health Research, Biomedical Research Centre for Ophthalmology, UCL Institute of Ophthalmology, Moorfields Eye Hospital City Road Campus, London, London, UK; p.keane{at}ucl.ac.uk

Abstract

Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has recently been discussed in the mainstream media and the literature with the advent of Generative Pre-trained Transformer 3 (GPT-3), a language model capable of producing human-like text. The release of GPT-3 has also sparked renewed interest on the applicability of NLP to contemporary healthcare problems. This article provides an overview of NLP models, with a focus on GPT-3, as well as discussion of applications specific to ophthalmology. We also outline the limitations of GPT-3 and the challenges with its integration into routine ophthalmic care.

  • Diagnostic tests/Investigation
  • Telemedicine

Data availability statement

Data sharing not applicable as no datasets generated and/or analysed for this study.

https://doi.org/10.1136/bjophthalmol-2022-321141

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    Data availability statement

    Data sharing not applicable as no datasets generated and/or analysed for this study.

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    Footnotes

    • Twitter @Sid_Nath, @pearsekeane

    • Contributors SN, AM and PAK conceived the review topic and identified relevant literature sources. SN, AM, SE, EK and PAK collaboratively wrote the manuscript. All authors reviewed and approved the final version of the article prior to submission.

    • Funding PAK is supported by a Moorfields Eye Charity Career Development Award (R190028A) and a UK Research & Innovation Future Leaders Fellowship (MR/T019050/1).

    • Competing interests EK has acted as a consultant for Google Health and Genentech and is an equity holder in Reti Health. PAK has acted as a consultant for DeepMind, Roche, Novartis, Apellis and BitFount, and is an equity owner in Big Picture Medical. He has received speaker fees from Heidelberg Engineering, Topcon, Allergan and Bayer.

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