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将人工智能整合到中风护理中的临床-AI相关性:一个系统化的文献审查和实践框架

João Brainer Clares de Andrade¹, Thiago S Carneiro², George N Nunes Mendes³

¹Universidade Federal de São Paulo, Department of Neurology, Department of Health Informatics, São Paulo, Brazil; Hospital Israelita Albert Einstein, Academic Research Organization, São Paulo, Brazil; Institute of Aeronautics Technology, Bioengineering Laboratory, São José dos Campos, Brazil.

International journal of medical informatics

|December 23, 2025

概括

在中风护理中的人工智能 (AI) 需要仔细整合. 一个新的框架指导神经科医生负责任地使用人工智能工具,确保患者安全和临床判断.

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:

人工智能在中风治疗中的快速采用超过了临床医生的理解.
需要对安全评估和实施人工智能工具的结构化指导.

研究的目的:

进行关于人工智能在中风护理方面的系统化文献综述.
为将人工智能负责任地整合到临床实践中制定一个实际框架.

主要方法:

对PubMed,EMBASE和灰色文献 (2018-2025) 的系统化审查.
使用QUADAS-2,RoB 2和ROBINS-I.使用偏差风险评估.
专家咨询神经病学家和人工智能开发人员.

主要成果:

152项研究符合纳入标准,重点关注大血管封闭检测,ASPECTS评分,结果预测,出血检测和治疗选择.
只有23%的研究具有低偏差风险,对选择偏差,混和验证存在担忧.
开发了临床-AI相关性框架,其三个支柱是:问题识别/工具选择,临床相关性和持续改进.

结论:

在中风护理中安全地整合人工智能,需要有结构的临床相关性和治理.
开发的框架有助于神经学家利用人工智能,同时保持临床判断和人类监督.
持续监测和记录人工智能与临床医生的互动对于安全实施至关重要.

关键词:

人工智能的人工智能是人工智能.脑卒中护理脑卒中护理血管神经学血管神经学

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