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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Mar 16, 2024
Date Accepted: Jul 11, 2024

The final, peer-reviewed published version of this preprint can be found here:

Practical Applications of Large Language Models for Health Care Professionals and Scientists

Reis F, Lenz C, Gossen M, Volk HD, Drzeniek NM

Practical Applications of Large Language Models for Health Care Professionals and Scientists

JMIR Med Inform 2024;12:e58478

DOI: 10.2196/58478

PMID: 39235317

PMCID: 11391657

Practical Applications of Large Language Models for Healthcare Professionals and Scientists

  • Florian Reis; 
  • Christian Lenz; 
  • Manfred Gossen; 
  • Hans-Dieter Volk; 
  • Norman Michael Drzeniek

ABSTRACT

With the popularization of Large Language Models (LLMs), strategies for their effective and safe utilization in healthcare and research become increasingly pertinent. Despite the growing interest and eagerness among healthcare professionals and scientists to exploit the potential of LLMs, initial attempts may yield suboptimal results due to a lack of user experience, thus complicating the integration of AI tools into workplace routine. This article showcases and discusses six LLM use cases of practical relevance for scientists and healthcare professionals. These encompass customizing translations, refining text and extracting information, generating comprehensive overviews and specialized insights, compiling ideas into cohesive narratives, crafting personalized educational materials, and facilitating intellectual sparring. Additionally, we discuss general prompting strategies and precautions for implementation of AI tools in biomedicine. Despite various challenges, the integration of LLMs into daily routines of physicians and researchers promises heightened workplace productivity and efficiency.


 Citation

Please cite as:

Reis F, Lenz C, Gossen M, Volk HD, Drzeniek NM

Practical Applications of Large Language Models for Health Care Professionals and Scientists

JMIR Med Inform 2024;12:e58478

DOI: 10.2196/58478

PMID: 39235317

PMCID: 11391657

Per the author's request the PDF is not available.

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