The integration of natural language processing (NLP) tools into neurology workflows has the potential to significantly enhance clinical care. However, it is important to address the limitations and risks associated with integrating this new technology. Recent advances in transformer-based NLP algorithms (e.g., GPT, BERT) could augment neurology clinical care by summarizing patient health information, suggesting care options, and assisting research involving large datasets. However, these NLP platforms have potential risks including fabricated facts and data security and substantial barriers for implementation. Although these risks and barriers need to be considered, the benefits for providers, patients, and communities are substantial. With these systems achieving greater functionality and the pace of medical need increasing, integrating these tools into clinical care may prove not only beneficial but necessary. Further investigation is needed to design implementation strategies, mitigate risks, and overcome barriers.

将自然语言处理 (NLP) 工具集成到神经病学工作流程中有可能显着增强临床护理。然而，解决与集成这项新技术相关的限制和风险非常重要。基于 Transformer 的 NLP 算法（例如 GPT、BERT）的最新进展可以通过总结患者健康信息、建议护理选择和协助涉及大型数据集的研究来增强神经病学临床护理。然而，这些NLP平台存在潜在的风险，包括伪造事实和数据安全以及巨大的实施障碍。尽管需要考虑这些风险和障碍，但对提供者、患者和社区的好处是巨大的。随着这些系统实现更强大的功能以及医疗需求的不断增加，将这些工具集成到临床护理中可能不仅是有益的，而且是必要的。需要进一步调查来设计实施策略、降低风险并克服障碍。