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设计中国医院急诊科以利用人工智能——关于挑战与机遇的系统文献综述

Designing Chinese hospital emergency departments to leverage artificial intelligence-a systematic literature review on the challenges and opportunities.

作者信息

Tan Sijie, Mills Grant

机构信息

Bartlett School of Sustainable Construction, Bartlett Faculty of the Built Environment, University College London, London, United Kingdom.

出版信息

Front Med Technol. 2024 Mar 21;6:1307625. doi: 10.3389/fmedt.2024.1307625. eCollection 2024.

Abstract

Artificial intelligence (AI) has witnessed rapid advances in the healthcare domain in recent years, especially in the emergency field, where AI is likely to radically reshape medical service delivery. Although AI has substantial potential to enhance diagnostic accuracy and operational efficiency in hospitals, research on its applications in Emergency Department building design remains relatively scarce. Therefore, this study aims to investigate Emergency Department facility design by identifying the challenges and opportunities of using AI. Two systematic literature reviews are combined, one in AI and the other in sensors, to explore their potential application to support decision-making, resource optimisation and patient monitoring. These reviews have then informed a discussion on integrating AI sensors in contemporary Emergency Department designs for use in China to support the evidence base on resuscitation units, emergency operating rooms and Emergency Department Intensive Care Unit (ED-ICU) design. We hope to inform the strategic implementation of AI sensors and how they might transform Emergency Department design to support medical staff and enhance the patient experience.

摘要

近年来,人工智能(AI)在医疗领域取得了飞速发展,尤其是在急诊领域,人工智能很可能会从根本上重塑医疗服务的提供方式。尽管人工智能在提高医院诊断准确性和运营效率方面具有巨大潜力,但关于其在急诊科建筑设计中的应用研究仍然相对较少。因此,本研究旨在通过识别使用人工智能的挑战和机遇来探讨急诊科设施设计。结合了两项系统文献综述,一项关于人工智能,另一项关于传感器,以探索它们在支持决策、资源优化和患者监测方面的潜在应用。这些综述随后引发了一场关于在中国当代急诊科设计中集成人工智能传感器的讨论,以支持关于复苏单元、急诊手术室和急诊科重症监护病房(ED-ICU)设计的证据基础。我们希望为人工智能传感器的战略实施提供信息,以及它们如何改变急诊科设计以支持医务人员并提升患者体验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42d5/10991761/293a30e97a98/fmedt-06-1307625-g001.jpg

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