Prompt Engineering Paradigms for Medical Applications: Scoping Review.

Journal: Journal of medical Internet research
Published Date: Sep 10, 2024

Abstract

BACKGROUND: Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language processing applications must navigate complex language and ensure privacy compliance. Prompt engineering offers a novel approach by designing tailored prompts to guide models in exploiting clinically relevant information from complex medical texts. Despite its promise, the efficacy of prompt engineering in the medical domain remains to be fully explored.

Authors

  • Jamil Zaghir
    Division of Medical Information Sciences, University Hospitals of Geneva.
  • Marco Naguib
    Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, Orsay, France.
  • Mina Bjelogrlic
    Division of Medical Information Sciences, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
  • Aurélie Névéol
  • Xavier Tannier
    Sorbonne Université, Inserm, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, 75006 Paris, France. Electronic address: xavier.tannier@sorbonne-universite.fr.
  • Christian Lovis
    Division of Medical Information Sciences Geneva University Hospitals and University of Geneva.

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