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可穿戴人工智能提升患者安全及临床决策能力。

Wearable AI to enhance patient safety and clinical decision-making.

作者信息

Mahajan Arjun, Heydari Kimia, Powell Dylan

机构信息

Harvard Medical School, Boston, MA, USA.

Faculty of Health Sciences & Sport, University of Stirling, Stirling, UK.

出版信息

NPJ Digit Med. 2025 Mar 22;8(1):176. doi: 10.1038/s41746-025-01554-w.

DOI:10.1038/s41746-025-01554-w
PMID:40121336
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11929813/
Abstract

Wearable artificial intelligence (AI) technologies show promise in healthcare, with early applications demonstrating diverse benefits for patient safety. These systems go beyond traditional data collection, using advanced algorithms to provide real-time clinical guidance. From infectious disease monitoring to AI-powered surgical assistance, these technologies enable proactive, personalized care while addressing critical safety gaps. However, successful implementation requires careful consideration of technical, operational, and ethical challenges.

摘要

可穿戴人工智能(AI)技术在医疗保健领域展现出了前景,早期应用已证明对患者安全具有多种益处。这些系统超越了传统的数据收集方式,利用先进算法提供实时临床指导。从传染病监测到人工智能辅助手术,这些技术在填补关键安全漏洞的同时,还能实现主动、个性化的护理。然而,要成功实施这些技术,需要仔细考虑技术、操作和伦理方面的挑战。

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Longitudinal analysis of a dominantly inherited Alzheimer disease mutation carrier protected from dementia.对一名受显性遗传阿尔茨海默病突变影响但未患痴呆症的携带者进行纵向分析。
Nat Med. 2025 Apr;31(4):1267-1275. doi: 10.1038/s41591-025-03494-0. Epub 2025 Feb 10.
3
Artificial intelligence for direct-to-physician reporting of ambulatory electrocardiography.
人工智能在类风湿关节炎、轴性脊柱关节炎和银屑病关节炎管理中的当前应用、可能性及挑战。
Ther Adv Musculoskelet Dis. 2025 Jun 21;17:1759720X251343579. doi: 10.1177/1759720X251343579. eCollection 2025.
用于动态心电图直接向医生报告的人工智能技术。
Nat Med. 2025 Mar;31(3):925-931. doi: 10.1038/s41591-025-03516-x. Epub 2025 Feb 10.
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Improving authenticity and provenance in digital biomarkers: the case for digital watermarking.提高数字生物标志物的真实性和来源可追溯性:数字水印的应用案例
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