Implementing large language models in healthcare while balancing control, collaboration, costs and security.
expert_opinion · Level V
Where this comes from
- Record sourced from PubMed, PMID 40050366.
- Also identified by DOI 10.1038/s41746-025-01476-7 and PMC identifier 11885444.
- Licence recorded as CC BY-NC-ND.
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Abstract
Integrating Large Language Models (LLMs) into healthcare promises substantial advancements but requires careful consideration of technical, ethical, and regulatory challenges. Closed LLMs of private companies offer ease of deployment but pose risks related to data privacy and vendor dependence. Open LLMs deployed on local hardware enable greater model customization but demand resources and technical expertise. Balancing these approaches, with collaboration among clinicians, researchers, and companies is crucial to ensure effective, secure, and ethical implementation.