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吞咽护理中从筛查到康复的数字健康技术:一项叙述性综述。

Digital health technologies in swallowing care from screening to rehabilitation: A narrative review.

作者信息

Alter Isaac L, Dias Carla, Briano Jack, Rameau Anaïs

机构信息

Department of Otolaryngology-Head and Neck Surgery, Sean Parker Institute for the Voice, Weill Cornell Medical College, 240 E 59 St, NY, NY 10022, USA.

Department of Otolaryngology-Head and Neck Surgery, Sean Parker Institute for the Voice, Weill Cornell Medical College, 240 E 59 St, NY, NY 10022, USA.

出版信息

Auris Nasus Larynx. 2025 May 21;52(4):319-326. doi: 10.1016/j.anl.2025.05.002.


DOI:10.1016/j.anl.2025.05.002
PMID:40403345
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12354047/
Abstract

OBJECTIVES: Digital health technologies (DHTs) have rapidly advanced in the past two decades, through developments in mobile and wearable devices and most recently with the explosion of artificial intelligence (AI) capabilities and subsequent extension into the health space. DHT has myriad potential applications to deglutology, many of which have undergone promising investigations and developments in recent years. We present the first literature review on applications of DHT in swallowing health, from screening to therapeutics. Public health interventions for swallowing care are increasingly needed in the setting of aging populations in the West and East Asia, and DHT may offer a scalable and low-cost solution. METHODS: A narrative review was performed using PubMed and Google Scholar to identify recent research on applications of AI and digital health in swallow practice. Database searches, conducted in September 2024, included terms such as "digital," "AI," "machine learning," "tools" in combination with "deglutition," "Otolaryngology," "Head and Neck," "speech language pathology," "swallow," and "dysphagia." Primary literature pertaining to digital health in deglutology was included for review. RESULTS: We review the various applications of DHT in swallowing care, including prevention, screening, diagnosis, treatment planning and rehabilitation. CONCLUSION: DHT may offer innovative and scalable solutions for swallowing care as public health needs grow and in the setting of limited specialized healthcare workforce. These technological advances are also being explored as time and resource saving solutions at many points of care in swallow practice. DHT could bring affordable and accurate information for self-management of dysphagia to broader patient populations that otherwise lack access to expert providers.

摘要

目标:在过去二十年中,数字健康技术(DHTs)迅速发展,这得益于移动和可穿戴设备的进步,以及最近人工智能(AI)能力的爆发并随后扩展到健康领域。DHT在吞咽学方面有无数潜在应用,其中许多在近年来已进行了前景良好的研究和开发。我们首次对DHT在吞咽健康中的应用进行文献综述,涵盖从筛查到治疗的各个方面。在东亚和西方老龄化人口背景下,对吞咽护理的公共卫生干预需求日益增加,而DHT可能提供一种可扩展且低成本的解决方案。 方法:使用PubMed和谷歌学术进行叙述性综述,以识别关于AI和数字健康在吞咽实践中应用的最新研究。2024年9月进行的数据库搜索包括“数字”“AI”“机器学习”“工具”等术语,与“吞咽”“耳鼻喉科”“头颈”“言语语言病理学”“吞咽”和“吞咽困难”相结合。纳入有关吞咽学中数字健康的原始文献进行综述。 结果:我们综述了DHT在吞咽护理中的各种应用,包括预防、筛查、诊断、治疗规划和康复。 结论:随着公共卫生需求的增长以及专业医疗劳动力有限,DHT可能为吞咽护理提供创新且可扩展的解决方案。这些技术进步也正在吞咽实践中的许多护理环节被探索为节省时间和资源的解决方案。DHT可以为更广泛的患者群体带来负担得起且准确的吞咽困难自我管理信息,而这些患者群体原本无法获得专家服务。

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引用本文的文献

[1]
Artificial intelligence in dysphagia since the 21st century: a bibliometric and visualization study.

Front Med (Lausanne). 2025-8-18

本文引用的文献

[1]
Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis.

Comput Methods Programs Biomed. 2025-7

[2]
Endoscopic and videofluoroscopic evaluations of swallowing for dysphagia: A systematic review.

Braz J Otorhinolaryngol. 2025-4-9

[3]
Development and Validation of a GULP-Based Predictive Model for Dehydration in Elderly Patients with Post-Stroke Dysphagia.

Br J Hosp Med (Lond). 2025-1-24

[4]
Development and validation of an electronic Symbol-Digit Modalities Test for remote monitoring of people with multiple sclerosis.

Eur J Neurol. 2025-1

[5]
Exploratory analysis of swallowing behaviour in community-dwelling older adults using a wearable device: Differences by age and ingestant under different task loads.

Digit Health. 2024-7-25

[6]
Autonomous Robotic Systems in Otolaryngology-Head and Neck Surgery.

Otolaryngol Clin North Am. 2024-10

[7]
The Development of an Artificial Intelligence Video Analysis-Based Web Application to Diagnose Oropharyngeal Dysphagia: A Pilot Study.

Brain Sci. 2024-5-27

[8]
Clinical evaluation of a machine learning-based dysphagia risk prediction tool.

Eur Arch Otorhinolaryngol. 2024-8

[9]
Computer-aided diagnosis improves characterization of Barrett's neoplasia by general endoscopists (with video).

Gastrointest Endosc. 2024-10

[10]
Definitions of digital biomarkers: a systematic mapping of the biomedical literature.

BMJ Health Care Inform. 2024-4-8

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