Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review.
Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review.
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DOI：
10.1177/2150132720963634
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发表时间：
2020-01
影响因子：
3.6
通讯作者：
Ibrahim MT
中科院分区：
文献类型：
--
作者：
Naseem M;Akhund R;Arshad H;Ibrahim MT
面对当前具有时间敏感性的COVID-19疫情，医疗系统的能力有限，因此需要开发新的方法来控制疫情的传播。人工智能（AI）和机器学习（ML）具有巨大的潜力，可以指数级优化医疗保健研究。在LMIC中使用人工智能驱动的工具可以帮助消除健康不平等并减轻卫生系统的负担。通过PubMed数据库使用关键词：COVID-19、人工智能（AI）、机器学习（ML）和中低收入国家（LMIC）进行了本次范围审查的文献检索。确定并筛选了43篇文章的合格性，13篇被纳入最终审查。本次范围界定审查的所有项目均使用PRISMA范围界定审查扩展指南（PRISMA-ScR）进行报告。在4个主题下综合和报告了结果。(a)在此大流行期间对人工智能的需求：人工智能可协助提高病例识别的速度和准确性，并通过数据挖掘有效应对健康危机。（B）人工智能在COVID-19筛查、接触者追踪和诊断中的应用：通过部署使用终端跟踪系统的智能城市数据网络以及预测未来爆发，可以提高病毒检测的效率，（c）人工智能在COVID-19患者监测和药物开发中的应用：深度学习系统提供了有关与COVID-19相关的蛋白质结构的宝贵信息，可用于疫苗配制，以及（d）COVID-19之后的人工智能和中低收入国家的机会：在LMIC缺乏财力、物力和人力资源的情况下，人工智能可以最大限度地减少人力劳动的工作量，并帮助分析大量的医疗数据，加强预测性和预防性医疗保健。基于人工智能的工具可以改变COVID-19患者的诊断、治疗和管理，并有可能重塑LMIC医疗保健的未来。
In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems. The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR). Results were synthesized and reported under 4 themes. (a) The need of AI during this pandemic: AI can assist to increase the speed and accuracy of identification of cases and through data mining to deal with the health crisis efficiently, (b) Utility of AI in COVID-19 screening, contact tracing, and diagnosis: Efficacy for virus detection can a be increased by deploying the smart city data network using terminal tracking system along-with prediction of future outbreaks, (c) Use of AI in COVID-19 patient monitoring and drug development: A Deep learning system provides valuable information regarding protein structures associated with COVID-19 which could be utilized for vaccine formulation, and (d) AI beyond COVID-19 and opportunities for Low-Middle Income Countries (LMIC): There is a lack of financial, material, and human resources in LMIC, AI can minimize the workload on human labor and help in analyzing vast medical data, potentiating predictive and preventive healthcare. AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC.