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Understanding Large Language Models in Healthcare: A Guide to Clinical Implementation and Interpreting Publications.

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This summary is machine-generated.

Large language models (LLMs) offer significant potential in healthcare. This review clarifies LLM terminology, evaluation methods, and applications to help healthcare professionals understand this AI technology.

Keywords:
artificial intelligence in medicinedeep learning artificial intelligencehealth professional's educationlarge language models (llms)large language models (llms) in medicineresearch

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Area of Science:

  • Artificial Intelligence in Medicine
  • Natural Language Processing
  • Clinical Informatics

Background:

  • Large language models (LLMs) are rapidly advancing, showing potential to transform healthcare delivery.
  • The increasing volume of LLM research necessitates clear understanding of terminology and applications for healthcare professionals.
  • Bridging the knowledge gap in LLM capabilities is crucial for effective clinical and administrative adoption.

Purpose of the Study:

  • To provide a comprehensive overview of the development and evolution of LLMs in the healthcare domain.
  • To define key terminologies associated with LLMs, enhancing comprehension for healthcare professionals.
  • To explore evaluation methodologies and practical applications of LLMs in healthcare settings.

Main Methods:

  • Literature review focusing on the evolution and application of LLMs in healthcare.
  • Systematic description of core LLM terminology and concepts relevant to medical professionals.
  • Analysis of experimental and research methodologies employed in LLM studies.
  • Illustrative examples of LLM applications in clinical and administrative healthcare scenarios.

Main Results:

  • LLMs present diverse opportunities for improving healthcare delivery through advanced AI.
  • Understanding LLM terminology and evaluation metrics is essential for clinicians.
  • Successful adoption requires consideration of both patient and healthcare professional perspectives.

Conclusions:

  • This review equips healthcare professionals with foundational knowledge of LLMs for research and practice.
  • Demystifying LLMs facilitates informed decision-making regarding their integration into healthcare systems.
  • LLMs represent a significant technological advancement with the potential to enhance patient care and operational efficiency.