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科学领域:

  • 神经成像是一种神经成像.
  • 医疗人工智能 医疗人工智能

背景情况:

  • 大脑动脉静脉形形 (AVMs) 需要准确的细分和治疗计划.
  • 目前的方法可能耗时,可能缺乏标准化.

研究的目的:

  • 系统地审查AI和ML用于AVM细分,量化和治疗规划的应用.
  • 评估AI/ML模型在AVM分析中的有效性.

主要方法:

  • 使用主要科学数据库进行了Prisma引导的系统审查.
  • 包括使用AI/ML进行基于成像的AVM分析的研究.

主要成果:

  • 分析了13项涉及3010个人的研究.
  • 常见的方法包括TOF-MRA和MRI,U-Net和SVM等模型.
  • AI/ML在风险评估,细分和立体术放射性手术规划方面表现出实用性,平均达到了0.758.8的Dice分数.

结论:

  • 人工智能和机器学习有可能提高AVM诊断和治疗的效率和标准化.
  • 临床实施受到模型通用性的限制;建议进行前性验证和多模式成像集成.