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人工智能用于预测异常性正常压力水头的穿反应:系统性审查

Rafael Tiza Fernandes¹, Filipe Wolff Fernandes², Mrinmoy Kundu³

¹Imperial Brain & Spine Initiative, Imperial College London, London, United Kingdom; Department of Neurosurgery, ULS São José, Lisbon, Portugal.

World neurosurgery

|September 23, 2024

概括

人工智能 (AI) 显示出预测异常性正常压力头症 (iNPH) 中的分离反应的潜力. 然而,需要进一步的研究来标准化数据,并验证AI模型在iNPH管理中临床使用.

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:

异常性正常压力脑症 (iNPH) 是一种可治疗的痴呆症原因,主要干预方法是分流手术.
对于iNPH的外科治疗结果有所不同,这突显了需要改进预测方法的需要.
人工智能 (AI) 通过分析复杂的患者数据集,提供了通过分析复杂的患者数据集来增强神经回应 (SR) 预测的潜力.

研究的目的:

系统地审查和评估AI在预测iNPH患者SR中的有效性.
确定目前用于iNPH中SR预测的AI和机器学习方法.
评估iNPH现有的AI模型的性能和局限性.

主要方法:

进行了一次系统的文献审查,搜索到MEDLINE,Embase和Web of Science,直到2023年9月.
在iNPH中使用人工智能或机器学习进行SR预测的研究被纳入,遵循PRISMA指南.
数据提取集中在AI算法,输入数据类型和报告的性能指标上.

主要成果:

八项涉及479名患者的研究符合纳入标准.
图像/放射学和人口统计是主要的数据输入;支持矢量机是最常见的算法.
报告的曲线下面面积值在0.80到0.94之间,但结果指标和潜在偏差存在显著的异质性.

结论:

人工智能在改善异常性正常压力头症的分流反应预测方面表现出有希望.
数据的标准化和AI模型的严格验证对于提高临床效用至关重要.
未来的研究应该专注于开发强大的,可通用的AI模型,以更有效地诊断和管理iNPH.

关键词:

人工智能的人工智能是人工智能.异常性正常压力水脑.正常压力水脑.预测预测预测关节反应的反应.在NPH中,iNPH是

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