We introduce a framework to adapt large language models for medicine: (1) Modeling: breaking down medical workflows into manageable steps; (2) Optimization: optimizing model performance via advanced adaptations; and (3) System engineering: developing agent or chain systems. Furthermore, we describe varied use cases, such as clinical trial design, clinical decision support, and medical imaging analysis. Finally, we discuss challenges and considerations for building medical AI with LLMs.
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Wang et al. (2025) studied this question.
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