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相关概念视频

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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相关实验视频

Updated: Jun 20, 2025

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
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自动算法用于医疗数据结构,并使用人工智能在安全环境中进行细分,以创建数据集.

Varatharajan Nainamalai1, Hemin Ali Qair1, Egidijus Pelanis1,2

  • 1The Intervention Centre, Rikshospitalet, Oslo University Hospital, Oslo, Norway.

European journal of radiology open
|July 23, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种半自动的工作流来管理医疗数据,利用人工智能 (AI) 来构建电子健康记录,并为研究创建准确的AI地面真相标签.

关键词:
人工智能的人工智能是人工智能.电子健康记录是电子健康记录.基础真理 创造创造分段化 分段化 分段化 分段化结构化数据结构化数据结构化数据

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科学领域:

  • 医疗信息学 医疗信息学
  • 医疗保健中的人工智能
  • 数据管理数据管理

背景情况:

  • 电子健康记录 (EHR) 包含大量的非结构化数据.
  • 人工智能 (AI) 提供了结构化各种数据类型的潜力.
  • 有效的医疗数据管理对于研究和临床应用至关重要.

研究的目的:

  • 为医疗数据集管理提供半自动化工作流.
  • 展示AI在结构化非结构化医疗数据中的作用.
  • 为了促进人工智能基础真相标签的创建,用于研究.

主要方法:

  • 开发了一种半自动的工作流程,用于数据结构化,研究提取和AI地面真相创建.
  • 实现了一个算法,根据文件名称关键字组织数据目录.
  • 利用人工智能模型进行初始标签生成,并对地面真相进行手动验证.

主要成果:

  • 成功组织了计算机断层扫描 (CT),磁共振 (MR) 图像,临床数据和注释.
  • 产生了最初的AI标签,这些标签被手动改进成基本真相标签.
  • 将经过验证的实地真相标签集成到一个结构化数据集中,用于未来的研究.

结论:

  • 提出的工作流程使得医疗数据集的高效管理成为可能.
  • 人工智能模型可以在当地医院的数据上进行训练,以获得量身定制的输出.
  • 自动化算法和人工智能可以在医院内安全地实现数据处理.