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人工智能在电子健康领域相关的汇聚技术综述。

A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence.

机构信息

Department of Electric, Electronic and Computer Engineering, Technical University of Cluj-Napoca, North University Center of Baia Mare, 430083 Baia Mare, Romania.

Department of IT Systems and Networks, Faculty of Informatics, University of Debrecen, 4032 Debrecen, Hungary.

出版信息

Int J Environ Res Public Health. 2022 Sep 10;19(18):11413. doi: 10.3390/ijerph191811413.


DOI:10.3390/ijerph191811413
PMID:36141685
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9517043/
Abstract

Over the last couple of years, in the context of the COVID-19 pandemic, many healthcare issues have been exacerbated, highlighting the paramount need to provide both reliable and affordable health services to remote locations by using the latest technologies such as video conferencing, data management, the secure transfer of patient information, and efficient data analysis tools such as machine learning algorithms. In the constant struggle to offer healthcare to everyone, many modern technologies find applicability in eHealth, mHealth, telehealth or telemedicine. Through this paper, we attempt to render an overview of what different technologies are used in certain healthcare applications, ranging from remote patient monitoring in the field of cardio-oncology to analyzing EEG signals through machine learning for the prediction of seizures, focusing on the role of artificial intelligence in eHealth.

摘要

在过去的几年中,在 COVID-19 大流行的背景下,许多医疗保健问题恶化了,这凸显了迫切需要利用视频会议、数据管理、患者信息安全传输以及机器学习算法等最新技术,为偏远地区提供可靠和负担得起的医疗服务。在努力为每个人提供医疗保健的过程中,许多现代技术在电子健康、移动健康、远程医疗或远程医疗中找到了应用。通过本文,我们试图概述在某些医疗保健应用中使用的不同技术,从心血管肿瘤学领域的远程患者监测到通过机器学习分析 EEG 信号以预测癫痫发作,重点介绍人工智能在电子健康中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/191a/9517043/a6a9fd486cfd/ijerph-19-11413-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/191a/9517043/a6a9fd486cfd/ijerph-19-11413-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/191a/9517043/a6a9fd486cfd/ijerph-19-11413-g001.jpg

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引用本文的文献

[1]
Sustainable E-Health: Energy-Efficient Tiny AI for Epileptic Seizure Detection via EEG.

Biomed Eng Comput Biol. 2025-8-10

[2]
Bridging Gaps in Telemedicine Education in Romania to Support Future Health Care: Scoping Review.

JMIR Med Educ. 2025-5-14

[3]
Exploring the evolution of eHealth in disease management: A bibliometric analysis from 1999 to 2023.

Digit Health. 2024-10-21

[4]
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Digit Health. 2024-9-27

[5]
eHealth Assistant AI Chatbot Using a Large Language Model to Provide Personalized Answers through Secure Decentralized Communication.

Sensors (Basel). 2024-9-23

[6]
Remote Wearable Neuroimaging Devices for Health Monitoring and Neurophenotyping: A Scoping Review.

Biomimetics (Basel). 2024-4-16

[7]
The Constrained-Disorder Principle Assists in Overcoming Significant Challenges in Digital Health: Moving from "Nice to Have" to Mandatory Systems.

Clin Pract. 2023-8-20

本文引用的文献

[1]
A machine learning approach to small area estimation: predicting the health, housing and well-being of the population of Netherlands.

Int J Health Geogr. 2022-6-6

[2]
Artificial Intelligence-Based Family Health Education Public Service System.

Front Psychol. 2022-5-11

[3]
Wearables, telemedicine, and artificial intelligence in arrhythmias and heart failure: Proceedings of the European Society of Cardiology Cardiovascular Round Table.

Europace. 2022-10-13

[4]
Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease.

Eur Heart J. 2022-8-14

[5]
Consumer perceptions of telehealth for mental health or substance abuse: a Twitter-based topic modeling analysis.

JAMIA Open. 2022-4-27

[6]
: A Natural Language Processing-Based Digital Phenotyping Tool for Smart Monitoring of Suicidal Ideation.

Healthcare (Basel). 2022-4-8

[7]
Mobile health technology in atrial fibrillation.

Expert Rev Med Devices. 2022-4

[8]
Benefits of Integrating Telemedicine and Artificial Intelligence Into Outreach Eye Care: Stepwise Approach and Future Directions.

Front Med (Lausanne). 2022-3-11

[9]
Telehealth and Artificial Intelligence Insights into Healthcare during the COVID-19 Pandemic.

Healthcare (Basel). 2022-2-18

[10]
Evaluation of a virtual coaching system eHealth intervention: A mixed methods observational cohort study in the Netherlands.

Internet Interv. 2022-2-5

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