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

Abstract

Large language models (LLMs) have generated excitement and interest in their capability to impact various facets of healthcare delivery. However, the rapidly expanding literature on LLMs presents challenges in understanding recent work, associated terminology, and potential applications for healthcare professionals. In this review, we discuss the development and evolution of LLMs, especially in healthcare. We provide a description of the key terminologies associated with LLMs to improve the understanding of these terms and their application context in healthcare. Evaluation of the experiments and research related to LLMs is fundamentally important for clinicians. Thus, we provide a description of evaluation methodologies used in LLM research. Lastly, through illustrative examples of research in application of LLMs in healthcare, we showcase the opportunities to leverage this state-of-the-art artificial intelligence (AI) technique with considerations for clinical and administrative adoption both by the patients and healthcare professionals. Through this review, we hope to equip the healthcare professionals with the knowledge they need to understand LLM in healthcare research.

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