Large Language Model Architectures in Health Care: Scoping Review of Research Perspectives.

ABSTRACT:

Background

Large language models (LLMs) can support health care professionals in their daily work, for example, when writing and filing reports or communicating diagnoses. With the rise of LLMs, current research investigates how LLMs could be applied in medical practice and their benefits for physicians in clinical workflows. However, most studies neglect the importance of selecting suitable LLM architectures.

Objective

In this literature review, we aim to provide insights on the different LLM model architecture families (ie, Bidirectional Encoder Representations from Transformers [BERT]-based or generative pretrained transformer [GPT]-based models) used in previous research. We report on the suitability and benefits of different LLM model architecture families for various r

SUBMITTER: Leiser F 

PROVIDER: S-EPMC12226782 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature