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Artificial intelligence systems for complex decision-making in acute care medicine: a review

机译:用于急诊医学复杂决策的人工智能系统:综述

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摘要

The integration of artificial intelligence (AI) into acute care brings a new source of intellectual thought to the bedside. This offers great potential for synergy between AI systems and the human intellect already delivering care. This much needed help should be embraced, if proven effective. However, there is a risk that the present role of physicians and nurses as the primary arbiters of acute care in hospitals may be overtaken by computers. While many argue that this transition is inevitable, the process of developing a formal plan to prevent the need to pass control of patient care to computers should not be further delayed.The first step in the interdiction process is to recognize; the limitations of existing hospital protocols, why we need AI in acute care, and finally how the focus of medical decision making will change with the integration of AI based analysis. The second step is to develop a strategy for changing the focus of medical education to empower physicians to maintain oversight of AI. Physicians, nurses, and experts in the field of safe hospital communication must control the transition to AI integrated care because there is significant risk during the transition period and much of this risk is subtle, unique to the hospital environment, and outside the expertise of AI designers.AI is needed in acute care because AI detects complex relational time-series patterns within datasets and this level of analysis transcends conventional threshold based analysis applied in hospital protocols in use today. For this reason medical education will have to change to provide healthcare workers with the ability to understand and over-read relational time pattern centered communications from AI. Medical education will need to place less emphasis on threshold decision making and a greater focus on detection, analysis, and the pathophysiologic basis of relational time patterns. This should be an early part of a medical student’s education because this is what their hospital companion (the AI) will be doing.Effective communication between human and artificial intelligence requires a common pattern centered knowledge base. Experts in safety focused human to human communication in hospitals should lead during this transition process.
机译:将人工智能(AI)集成到急诊中,为床边带来了新的智力思想来源。这为AI系统和已经提供护理的人类智力之间的协同增效提供了巨大潜力。如果证明有效,则应该接受急需的帮助。但是,存在风险,即计算机可能会取代医生和护士目前作为医院急诊服务的主要仲裁者的角色。尽管许多人认为这种过渡是不可避免的,但是制定正式计划以防止将患者护理控制权转移给计算机的过程不应再被拖延。现有医院规程的局限性,为什么我们需要在急诊中使用AI,以及最终医疗决策的重点将随着基于AI的分析的集成而改变。第二步是制定策略来改变医学教育的重点,以使医师能够对AI进行监督。医院安全通信领域的内科医生,护士和专家必须控制向AI集成护理的过渡,因为在过渡期间存在很大的风险,并且这种风险中的大部分是微妙的,医院环境所特有的,并且超出了AI的专业知识急性护理需要AI,因为AI会检测数据集中的复杂关系时间序列模式,并且这一分析水平超越了目前在医院使用的基于阈值的常规分析方法。因此,医学教育将不得不改变,以使医护人员能够理解和过度阅读以AI为中心的以关系时间模式为中心的通信。医学教育将需要减少对阈值决策的重视,而应更多地关注关系时间模式的检测,分析和病理生理基础。这应该是医科学生教育的早期阶段,因为这是他们的医院同伴(AI)所要做的。人与人工智能之间的有效交流需要以共同模式为中心的知识库。在此过渡过程中,以安全为重点的专家应在医院中人与人之间的交流中发挥领导作用。

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