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相关概念视频

Issues And Trends In Healthcare Delivery System01:29

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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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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Updated: Jul 22, 2025

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在世界各地部署人工智能用于胸部成像.

Samantha Singh1, Ameena Elahi2, Alan Schweitzer3

  • 1Department of Radiology, Georgetown Public Hospital Corporation, Georgetown, Guyana.

Journal of the American College of Radiology : JACR
|July 24, 2023
PubMed
概括

胸部成像中的人工智能 (AI) 正在在低收入和中等收入国家 (LMICs) 中部署. 一个成功的三方策略涉及教育,基础设施和分阶段引入人工智能,在胸部X光学解释中显示出高一致率.

关键词:
人工智能的人工智能是人工智能.全球卫生健康全球卫生健康实施科学 实施科学低收入和中等收入国家.

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 全球健康 全球健康

背景情况:

  • 人工智能 (AI) 胸部成像应用越来越多地部署在低收入和中等收入国家 (LMICs).
  • 放射科医生在确保人工智能解决方案的有效和道德实施方面发挥着至关重要的作用.
  • 国际RAD-AID采用战略方法来应对LMIC人工智能实施中的挑战.

研究的目的:

  • 评估在圭亚那和尼日利亚的三级医院中用于胸部X射线 (CXR) 解释的AI软件的实施情况.
  • 评估三个方面实施战略的有效性:临床教育,基础设施和分阶段的AI引入.
  • 通过与放射科医生的解释进行本地比较来验证AI性能.

主要方法:

  • 在圭亚那和尼日利亚的两个高等医院部署了用于CXR解释的AI软件.
  • 实现了一个具有云功能的图片存档和通信系统 (PACS).
  • 对30名放射科住院医生和主治医生进行了AI入门课程.
  • 利用分阶段的AI引入进行本地验证和工作流集成.
  • 将AI输出与当地放射科医生的前性生成报告进行了比较.

主要成果:

  • 在两个机构成功安装了PACS.
  • 参与者在AI课程后 (75%至95%) 显著提高了知识水平.
  • 在圭亚那,人工智能和放射科医生之间的正常/异常发现达到了87%的一致性.
  • 在尼日利亚,AI和放射科医生之间实现了85%的结核病检测一致性.
  • 人工智能软件已成功部署,并在两个地点按预期使用.

结论:

  • 在LMICs中采用AI存在独特的障碍.
  • 参与当地机构和行业合作伙伴的合作实施策略对于成功部署人工智能至关重要.
  • 该研究展示了在资源有限的环境中实施AI的可行模型.