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本文引用的文献

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Association Between Primary Care Payment Model and Telemedicine Use for Medicare Advantage Enrollees During the COVID-19 Pandemic.初级保健支付模式与新冠疫情期间医疗保险优势计划参保者远程医疗使用之间的关联。
JAMA Health Forum. 2021 Jul 16;2(7):e211597. doi: 10.1001/jamahealthforum.2021.1597. eCollection 2021 Jul.
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'Personal Health Surveillance': The Use of mHealth in Healthcare Responsibilisation.“个人健康监测”:移动健康在医疗责任化中的应用
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Ethical Machine Learning in Healthcare.医疗保健中的伦理机器学习。
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When smartwatches contribute to health anxiety in patients with atrial fibrillation.当智能手表加剧房颤患者的健康焦虑时。
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Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review.智能设备和可穿戴技术在检测和监测精神健康状况及压力方面的应用:系统评价。
Sensors (Basel). 2021 May 16;21(10):3461. doi: 10.3390/s21103461.
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Wearable sensors enable personalized predictions of clinical laboratory measurements.可穿戴传感器可实现临床实验室测量的个性化预测。
Nat Med. 2021 Jun;27(6):1105-1112. doi: 10.1038/s41591-021-01339-0. Epub 2021 May 24.
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Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study.腕带可穿戴设备采集的重度抑郁症症状严重程度与睡眠的关系:多中心纵向观察性研究。
JMIR Mhealth Uhealth. 2021 Apr 12;9(4):e24604. doi: 10.2196/24604.
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The digital scribe in clinical practice: a scoping review and research agenda.临床实践中的数字抄写员:一项范围综述及研究议程。
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The emerging clinical role of wearables: factors for successful implementation in healthcare.可穿戴设备在临床领域的新角色:医疗保健领域成功应用的因素
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Smart wearable devices in cardiovascular care: where we are and how to move forward.智能可穿戴设备在心血管护理中的应用:现状与展望。
Nat Rev Cardiol. 2021 Aug;18(8):581-599. doi: 10.1038/s41569-021-00522-7. Epub 2021 Mar 4.

临床人工智能在社区儿科学中的前景与挑战。

The promises and challenges of clinical AI in community paediatric medicine.

作者信息

Singh Devin, Nagaraj Sujay, Daniel Ryan, Flood Colleen, Kulik Dina, Flook Robert, Goldenberg Anna, Brudno Michael, Stedman Ian

机构信息

Hospital for Sick Children, Toronto, Ontario, Canada.

Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.

出版信息

Paediatr Child Health. 2023 Mar 28;28(4):212-217. doi: 10.1093/pch/pxac080. eCollection 2023 Jul.

DOI:10.1093/pch/pxac080
PMID:37287484
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10243963/
Abstract

The widespread adoption of virtual care technologies has quickly reshaped healthcare operations and delivery, particularly in the context of community medicine. In this paper, we use the virtual care landscape as a point of departure to envision the promises and challenges of artificial intelligence (AI) in healthcare. Our analysis is directed towards community care practitioners interested in learning more about how AI can change their practice along with the critical considerations required to integrate AI into their practice. We highlight examples of how AI can enable access to new sources of clinical data while augmenting clinical workflows and healthcare delivery. AI can help optimize how and when care is delivered by community practitioners while also improving practice efficiency, accessibility, and the overall quality of care. Unlike virtual care, however, AI is still missing many of the key enablers required to facilitate adoption into the community care landscape and there are challenges we must consider and resolve for AI to successfully improve healthcare delivery. We discuss several critical considerations, including data governance in the clinic setting, healthcare practitioner education, regulation of AI in healthcare, clinician reimbursement, and access to both technology and the internet.

摘要

虚拟护理技术的广泛应用迅速重塑了医疗保健运营和服务,尤其是在社区医学背景下。在本文中,我们以虚拟护理领域为出发点,展望人工智能(AI)在医疗保健领域的前景与挑战。我们的分析针对有兴趣深入了解人工智能如何改变其实践以及将人工智能整合到其实践中所需的关键考虑因素的社区护理从业者。我们重点介绍了人工智能如何在增加临床工作流程和医疗服务的同时,能够获取新的临床数据源的示例。人工智能可以帮助优化社区从业者提供护理的方式和时间,同时还能提高实践效率、可及性和整体护理质量。然而,与虚拟护理不同,人工智能仍缺少许多促进其融入社区护理领域所需的关键推动因素,并且我们必须考虑并解决一些挑战,以便人工智能能够成功改善医疗服务。我们讨论了几个关键考虑因素,包括临床环境中的数据治理、医疗保健从业者教育、医疗保健领域人工智能的监管、临床医生报销以及技术和互联网的获取。