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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.
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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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可解释的人工智能:增强整形外科的决策能力.

Berk B Ozmen1, Victor F A Almeida2, Piyush Mathur2

  • 1Department of Plastic Surgery, Cleveland Clinic, Cleveland, OH, USA.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
|July 27, 2025
PubMed
概括
此摘要是机器生成的。

可解释的人工智能 (XAI) 使整形外科人工智能建议变得透明. 这通过澄清AI决策过程,提高了外科医生的信任和临床采用.

关键词:
临床决策支持 临床决策支持可解释的人工智能机器学习 机器学习患者为中心的护理整形外科手术 整形外科手术预测外科手术风险预测

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科学领域:

  • 医疗信息学 医疗信息学
  • 计算机科学 计算机科学
  • 整形外科 整形外科 整形外科

背景情况:

  • 人工智能 (AI) 模型越来越多地用于整形外科预测和规划.
  • 人工智能的"黑子"性质阻碍了外科医生的信任和临床采用.
  • 人工智能决策缺乏透明度,限制了它与外科手术工作流程的整合.

研究的目的:

  • 引入可解释的人工智能 (XAI) 方法用于整形手术.
  • 提高对外科医生的AI推的透明度和理解.
  • 促进人工智能融入临床实践,同时保持外科医生监督.

主要方法:

  • 概述XAI对个案解释的方法.
  • 介绍了从人工智能模型中生成人口层面见解的方法.
  • 描述适用于整形外科应用的可视化技术.

主要成果:

  • XAI将不透明的AI系统转化为透明的决策支持工具.
  • 方法使外科医生能够理解AI建议背后的推理.
  • 整合XAI增强了临床采用和外科医生对AI的信任.

结论:

  • XAI对于弥合人工智能能力和整形外科临床实践之间的差距至关重要.
  • 透明的AI决策支持使外科医生能够保持以患者为中心的护理.
  • 通过可靠的AI集成,XAI增强了整形外科的科学和艺术方面.