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相关概念视频

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
635

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在神经学中使用人工智能设备:绘制现在和未来的地图.

Ashwin Amurthur1,2, Davis J McCarthy3,4, Lee H Schwamm5

  • 1Department of Neurology, Mass General Brigham, Boston, Massachusetts, United States.

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概括

人工智能 (AI) 和机器学习 (ML) 医疗设备正在改变神经系统护理. 这篇评论分析了147个FDA授权的设备,并讨论了它们的整合和未来的影响.

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科学领域:

  • 神经学 神经学
  • 医疗技术 医疗技术 医学技术
  • 人工智能的人工智能

背景情况:

  • 在过去的十年中,神经病学AI和ML医疗设备的显著增长.
  • 这些技术越来越多地增强了临床工作流程和患者护理服务.

研究的目的:

  • 审查用于医疗设备的核心机器学习技术.
  • 描述2024年12月31日美国食品和药物管理局授权的支持人工智能的医疗设备.
  • 分析设备集成的趋势和对未来神经病理护理的影响.

主要方法:

  • 介绍基本的机器学习技术.
  • 对147个获得FDA授权的AI支持医疗器械进行分析.
  • 检查整合趋势和人机交互模型.

主要成果:

  • 已有147种支持人工智能的医疗设备获得了FDA对神经学和神经放射学指示的授权.
  • 确定了临床整合的关键趋势.
  • 突出了新兴的人机交互模型.

结论:

  • 人工智能和机器学习设备正在重塑神经学护理的提供.
  • 了解这些技术及其整合对于未来的实践至关重要.
  • 未来的神经治疗可能会涉及先进的人机协作.