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Artificial intelligence and large language models in palliative medicine clinical practice and education
  1. Mark Taubert1,
  2. Robyn Hackett2 and
  3. Simon Tavabie3
  1. 1Velindre Cancer Centre, Velindre NHS Trust, Cardiff, UK
  2. 2Velindre Cancer Centre, Cardiff, UK
  3. 3Palliative Medicine, The Royal London Hospital, London, UK
  1. Correspondence to Dr Simon Tavabie; simon.tavabie{at}nhs.net

Abstract

As we approach 2034, we anticipate significant advancements in digital technologies and their impact across various domains, including palliative and end-of-life care and perhaps higher education more generally. Predicting technological breakthroughs, especially in the realm of artificial intelligence (AI), is notoriously difficult. In a sense, you might need an AI to do this effectively. While some digital challenges can surprise us, others prove more elusive than expected. For example, AI’s ability to be creative with language and comprehension has been genuinely remarkable and will likely be of interest to those whose ‘bread and butter’ at work is communication. Similarly, those who teach skills required of clinicians in palliative and end-of-life care, including breaking bad news and nuanced conversations around holistic complexity and treatment preferences are likely to see significant changes and shifts in their practice.

  • End of life care
  • Palliative care
  • Education and training

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Footnotes

  • X @simontavabie

  • Contributors MT developed the concept and drafted the initial manuscript which was reviewed and honed by RH and ST. ST acts as guarantor.

  • 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.