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用于新型冠状病毒肺炎自我检测的区块链与人工智能技术

Blockchain and Artificial Intelligence Technology for Novel Coronavirus Disease-19 Self-Testing.

作者信息

Mashamba-Thompson Tivani P, Crayton Ellen Debra

机构信息

Department of Public Health, University of Limpopo, Polokwane, Limpopo Province 0727, South Africa.

Genesis Technology and Management Group, (GenesisTMG, LLC), Bethesda, MD 20817, USA.

出版信息

Diagnostics (Basel). 2020 Apr 1;10(4):198. doi: 10.3390/diagnostics10040198.


DOI:10.3390/diagnostics10040198
PMID:32244841
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7235895/
Abstract

The novel coronavirus disease 19 (COVID-19) is rapidly spreading with a rising death toll and transmission rate reported in high income countries rather than in low income countries. The overburdened healthcare systems and poor disease surveillance systems in resource-limited settings may struggle to cope with this COVID-19 outbreak and this calls for a tailored strategic response for these settings. Here, we recommend a low cost blockchain and artificial intelligence-coupled self-testing and tracking systems for COVID-19 and other emerging infectious diseases. Prompt deployment and appropriate implementation of the proposed system have the potential to curb the transmissions of COVID-19 and the related mortalities, particularly in settings with poor access to laboratory infrastructure.

摘要

新型冠状病毒肺炎(COVID-19)正在迅速传播,据报道,高收入国家的死亡人数和传播率在上升,而非低收入国家。资源有限地区负担过重的医疗系统和薄弱的疾病监测系统可能难以应对此次COVID-19疫情,这就需要针对这些地区制定量身定制的战略应对措施。在此,我们推荐一种低成本的区块链与人工智能相结合的COVID-19及其他新发传染病自我检测和追踪系统。迅速部署并妥善实施该系统有可能遏制COVID-19的传播及相关死亡,尤其是在实验室基础设施匮乏的地区。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e66a/7235895/993094228ca5/diagnostics-10-00198-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e66a/7235895/993094228ca5/diagnostics-10-00198-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e66a/7235895/993094228ca5/diagnostics-10-00198-g001.jpg

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本文引用的文献

[1]
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AIDS Care. 2021-4

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Diagnostics (Basel). 2017-11-29

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Development and Testing of a Mobile Phone App for Self-Monitoring of Calcium Intake in Young Women.

JMIR Mhealth Uhealth. 2017-3-7

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[10]
Will an unsupervised self-testing strategy for HIV work in health care workers of South Africa? A cross sectional pilot feasibility study.

PLoS One. 2013-11-27

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