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