医学领域中大型语言模型的创建与采用。
Creation and Adoption of Large Language Models in Medicine.
机构信息
Stanford Health Care, Palo Alto, California.
Department of Medicine, School of Medicine, Stanford University, Stanford, California.
出版信息
JAMA. 2023 Sep 5;330(9):866-869. doi: 10.1001/jama.2023.14217.
IMPORTANCE
There is increased interest in and potential benefits from using large language models (LLMs) in medicine. However, by simply wondering how the LLMs and the applications powered by them will reshape medicine instead of getting actively involved, the agency in shaping how these tools can be used in medicine is lost.
OBSERVATIONS
Applications powered by LLMs are increasingly used to perform medical tasks without the underlying language model being trained on medical records and without verifying their purported benefit in performing those tasks.
CONCLUSIONS AND RELEVANCE
The creation and use of LLMs in medicine need to be actively shaped by provisioning relevant training data, specifying the desired benefits, and evaluating the benefits via testing in real-world deployments.
重要性
人们对在医学中使用大型语言模型（LLMs）越来越感兴趣，并可能从中受益。然而，如果只是想知道这些 LLM 以及由它们驱动的应用程序将如何重塑医学，而不积极参与其中，那么在塑造这些工具在医学中的使用方式方面就会失去主导权。
观察结果
越来越多的应用程序由 LLM 驱动，用于执行医学任务，而这些 LLM 并未在医疗记录上进行训练，也没有验证它们在执行这些任务时的所谓益处。
结论和相关性
在医学中创建和使用 LLM 需要积极提供相关的训练数据，指定所需的益处，并通过在实际部署中进行测试来评估这些益处。
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