October 12, 2025Open Access

Understanding the Inner Workings of Large Language Models in Medicine

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Analysis demonstrates how transformer architecture enhances medical reasoning in practice, suggesting key competencies for effective use.

Understanding transformer architecture enhances the interpretation of large language model outputs in medicine, improving diagnostic accuracy.
Five critical topics in medical reasoning arise from large language models, including identifying hallucinations and explaining ambiguous responses.
A theoretical understanding of large language models supports responsible clinical integration, highlighting risks in differential diagnosis.
Training in ethical and practical application of large language models in healthcare is essential for leveraging their capabilities and mitigating risks.

Fuellen et al. (2025) studied this question.

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