Evaluation shows performance inconsistencies in large language models for clinical chemistry and immunology, highlighting the need for further development.
LLMs demonstrated substantial potential for integration into laboratory medicine, particularly in clinical chemistry and immunology. Performance inconsistencies (particularly for high-difficulty questions) and knowledge gaps (notably for transfusion medicine) highlight the necessity for further development-potentially including domain-specific fine-tuning and retrieval-augmented generation integration-and robust expert oversight before clinical application.
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Jung et al. (2025) studied this question.
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