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The Recent Progress and Applications of Digital Technologies in Healthcare: A Review.

作者信息

Senbekov Maksut, Saliev Timur, Bukeyeva Zhanar, Almabayeva Aigul, Zhanaliyeva Marina, Aitenova Nazym, Toishibekov Yerzhan, Fakhradiyev Ildar

机构信息

S.D. Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.

NJSC "Astana Medical University", Nur-Sultan, Kazakhstan.

出版信息

Int J Telemed Appl. 2020 Dec 3;2020:8830200. doi: 10.1155/2020/8830200. eCollection 2020.


DOI:10.1155/2020/8830200
PMID:33343657
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7732404/
Abstract

BACKGROUND: The implementation of medical digital technologies can provide better accessibility and flexibility of healthcare for the public. It encompasses the availability of open information on the health, treatment, complications, and recent progress on biomedical research. At present, even in low-income countries, diagnostic and medical services are becoming more accessible and available. However, many issues related to digital health technologies remain unmet, including the reliability, safety, testing, and ethical aspects. PURPOSE: The aim of the review is to discuss and analyze the recent progress on the application of big data, artificial intelligence, telemedicine, block-chain platforms, smart devices in healthcare, and medical education. . The publication search was carried out using Google Scholar, PubMed, Web of Sciences, Medline, Wiley Online Library, and CrossRef databases. The review highlights the applications of artificial intelligence, "big data," telemedicine and block-chain technologies, and smart devices (internet of things) for solving the real problems in healthcare and medical education. . We identified 252 papers related to the digital health area. However, the number of papers discussed in the review was limited to 152 due to the exclusion criteria. The literature search demonstrated that digital health technologies became highly sought due to recent pandemics, including COVID-19. The disastrous dissemination of COVID-19 through all continents triggered the need for fast and effective solutions to localize, manage, and treat the viral infection. In this regard, the use of telemedicine and other e-health technologies might help to lessen the pressure on healthcare systems. . Digital platforms can help optimize diagnosis, consulting, and treatment of patients. However, due to the lack of official regulations and recommendations, the stakeholders, including private and governmental organizations, are facing the problem with adequate validation and approbation of novel digital health technologies. In this regard, proper scientific research is required before a digital product is deployed for the healthcare sector.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/9df6aa284e55/IJTA2020-8830200.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/394788c23f18/IJTA2020-8830200.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/70c8c8a632ba/IJTA2020-8830200.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/ddac992c3132/IJTA2020-8830200.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/9df6aa284e55/IJTA2020-8830200.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/394788c23f18/IJTA2020-8830200.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/70c8c8a632ba/IJTA2020-8830200.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/ddac992c3132/IJTA2020-8830200.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9b6/7732404/9df6aa284e55/IJTA2020-8830200.004.jpg

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本文引用的文献

[1]
Cost-effectiveness of Interventions to Manage Diabetes: Has the Evidence Changed Since 2008?

Diabetes Care. 2020-7

[2]
Implications of artificial intelligence for medical education.

Lancet Digit Health. 2020-3

[3]
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Cureus. 2020-8-20

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Digit Health. 2020-8-30

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Am Heart J. 2020-7-16

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The Next Frontier in Pediatric Cardiology: Artificial Intelligence.

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Physica A. 2020-11-1

[8]
Digital Response During the COVID-19 Pandemic in Saudi Arabia.

J Med Internet Res. 2020-9-1

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Crit Care. 2020-7-30

[10]
Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects.

J Infect Public Health. 2020-7-1

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