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相关概念视频

Hearing01:31

Hearing

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When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.
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相关实验视频

Updated: May 12, 2025

Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique
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对于听力障碍数据基础设施 (HEIDI) 研究的一项协议.

Yvonne Tran1, Mariano Cabezas1, Frank Tran1

  • 1Macquarie University Hearing Research Centre, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia.

PloS one
|May 7, 2025
PubMed
概括
此摘要是机器生成的。

这项研究建立了听力障碍数据基础设施 (HEIDI) 数据湖,以分析听力损失患者的护理途径. 这些发现将有助于更好地了解听力损失管理和患者旅程.

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Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
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科学领域:

  • 医疗信息学 医疗信息学
  • 数据科学数据科学数据科学
  • 听力学 听力学是指听力学.

背景情况:

  • 早期发现和治疗听力损失对于减轻负面影响至关重要.
  • 现实世界的数据,包括电子健康记录,为听力损失管理提供了宝贵的见解.
  • 听力障碍数据基础设施 (HEIDI) 项目旨在整合各种数据集,以研究患者护理途径.

研究的目的:

  • 通过整合来自全科医院,听力学诊所和队列研究的数据来构建HEIDI数据湖.
  • 调查听力损失患者的护理途径,从全科医院到听力学服务.
  • 回答有关患者导航听力损失护理旅程的关键研究问题.

主要方法:

  • 建立一个安全的HEIDI数据湖,符合澳大利亚隐私法规.
  • 通过数据链接,整合听力和通用实践数据集.
  • 开发HEIDI数据仓库,使用统计技术和机器学习进行描述和预测分析.

主要成果:

  • 描述性分析将阐明患者的旅程,并确定听力损失护理的趋势.
  • 使用机器学习的预测分析将识别患者进行主动管理.
  • 将确定干预措施和患者旅程里程碑对结果的影响.

结论:

  • HEIDI数据湖将为了解和改善听力损失护理提供一个强大的平台.
  • 该项目将加强识别那些可能受益于及时干预的患者.
  • 调查结果将为更有效的听力损失管理和患者支持策略提供信息.