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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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手术研究中的人工智能:成功实施AI临床决策支持模型

Jeff Choi1

  • 1From the Division of General Surgery, Department of Surgery, Stanford University, Stanford, California.

The journal of trauma and acute care surgery
|July 3, 2025
PubMed
概括

在外科手术中实施人工智能 (AI) 需要从一开始就考虑现实世界的应用. 这种方法确保AI临床决策支持模型是值得信赖和可操作的,弥合了从开发到床边使用的差距.

科学领域:

  • 手术创新 在外科创新.
  • 临床决策支持系统 临床决策支持系统
  • 人工智能在医学中的应用

背景情况:

  • 目前在外科手术中的人工智能 (AI) 研究重点是决策支持模型.
  • 尽管有众多的开发和验证研究,但人工智能模型的成功临床实施仍然有限.
  • 现有的指导方针 (TRIPOD-AI,DECIDE-AI) 单独处理开发/验证和分阶段实施.

研究的目的:

  • 建议从AI模型开发的开始就整合实施考虑因素.
  • 为设计可信且可操作的AI临床决策支持模型提供指导.
  • 解决解决人工智能实施的数据库到床边差距的挑战.

主要方法:

  • 从高性能人工智能决策支持模型中吸取的经验教训与实施挑战的回顾.
  • 讨论未来人工智能模型开发的研究设计考虑因素.
  • 对在临床实践中成功实施人工智能的因素进行分析.

主要成果:

  • 很少有人工智能模型在实施后实现其预期目标.
  • 尽管有强大的开发和验证,但实施挑战往往会出现.
  • 积极考虑实施对于人工智能成功至关重要.

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结论:

  • 未来的AI临床决策支持模型需要改变范式,在开发之前整合实施计划.
  • 设计可靠性和可操作性是成功在手术中采用人工智能的关键.
  • 解决数据库到床边的差距需要从创建到部署的整体方法.