Expert-Guided Large Language Models for Clinical Decision Support in Precision Oncology

Key Points

This research explores how expert guidance and specific data improve the performance of large language models in oncology.
Leveraged expert feedback to enhance model training.
Incorporated domain-specific data for clinical applications.
Evaluated the performance of LLMs in decision-making scenarios.
Expert-guided LLMs showed improved accuracy in clinical decision support.
Significant performance gains were observed compared to standard models.
Integration of LLMs into clinical workflows was suggested as a future research direction.

Investigates large language models for clinical decision support in precision oncology, suggesting enhanced performance with expert input.

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Lammert et al. (2024) studied this question.

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