Large language models in real-world clinical workflows: a systematic review of applications and implementation

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LLMs showed notable improvements in operational efficiency and user satisfaction within clinical workflows.
Four peer-reviewed studies from 2024 to 2025 assessed LLMs, utilizing generative pre-trained transformers for various tasks.
A systematic review was conducted across several databases, emphasizing empirical implementations and limitations of LLMs.
Significant barriers to adoption include regulatory delays, performance variability, and the need for tailored implementation frameworks.

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Systematic review evaluates applications and challenges of large language models in clinical workflows, highlighting key barriers.

Artsi et al. (2025) studied this question.

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