用自然语言处理工具改善神经病学临床护理

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Wendong Ge¹, Hunter J Rice¹, Irfan S Sheikh¹

¹From the Department of Neurology (W.G., H.J.R., I.S.S., L.M.), Massachusetts General Hospital, Boston; Department of Neurology (M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Information Technology Division (A.L.W.), Cleveland Clinic, OH; Department of Neurology (L.K.J.), Mayo Clinic, Rochester, MN; and Department of Neurology (L.M.), Harvard Medical School, Boston, MA.

|October 10, 2023

概括

自然语言处理 (NLP) 工具可以通过总结数据和帮助研究来改善神经病治疗. 然而,虚构事实和数据安全等风险需要谨慎管理才能成功整合.

科学领域:

神经学神经学
医疗信息学医疗信息学
人工智能的人工智能

背景情况:

自然语言处理 (NLP) 工具为临床护理提供了潜在的好处.
基于变压器的NLP算法 (例如GPT,BERT) 在增强神经病学工作流程方面表现有前途.

研究的目的:

探索NLP工具在神经学中的整合.
确定在临床神经学中实施NLP的潜在好处,风险和障碍.

主要方法:

审查基于变压器的NLP算法的最近进展.
分析潜在的应用在总结患者健康信息,建议护理选择,并协助研究.
考虑实施障碍和风险,如数据安全和伪造的事实.

主要成果:

通过总结患者数据,建议治疗方法和帮助大数据集的研究,NLP可以增强神经学.
潜在的风险包括数据安全漏洞和生成不准确信息.
在临床环境中存在重大实施障碍.

结论:

尽管存在风险和障碍,NLP整合为神经病学提供者,患者和社区提供了巨大的好处.
随着NLP系统的功能和医疗需求日益增加,整合可能变得必不可少.
需要进一步的研究来制定有效实施,降低风险和克服障碍的战略.

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