Evaluating large language models as clinical laboratory test recommenders in primary and emergency care: a crucial step in clinical decision making

Abstract

This work underscores the promise of LLMs in optimizing laboratory test ordering while identifying gaps for enhancing their alignment with clinical practice. Future research should focus on real-world implementation, integrating clinician feedback, and ensuring alignment with local test menus and guidelines to improve both performance and trust in LLM-driven clinical decision support.

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