通过合理的数据共享，加速全球应对呈指数级增长的 COVID-19 疫情的反应。
Accelerating the global response against the exponentially growing COVID-19 outbreak through decent data sharing.
机构信息
Biophysics program, Stanford Medical School, Stanford, CA, USA; International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan.
Working Groups and SIGs, International Medical Informatics Association; Graduate Institute of Biomedical Informatics, College of Medical Science & Technology, Taipei Medical University, Taipei, Taiwan; Salumedia Labs, Sevilla, Spain.
出版信息
Diagn Microbiol Infect Dis. 2021 Oct;101(2):115070. doi: 10.1016/j.diagmicrobio.2020.115070. Epub 2020 May 7.
Abstract
The novel coronavirus disease 2019 (COVID-19) is a novel and exponentially growing disease, and consequently, the accelerated development of knowledge from good data is possible quickly and globally. In order to combat the global pandemic of COVID-19, all humans on earth need to make difficult strategic decisions on three very different scales, all fueled by Analytical and Artificial Intelligence-based predictive Models.
摘要
2019 年新型冠状病毒病（COVID-19）是一种新型的、呈指数级增长的疾病，因此，从高质量数据中快速、全球地加速知识发展是可能的。为了应对 COVID-19 的全球大流行，地球上所有人类都需要在三个非常不同的尺度上做出艰难的战略决策，所有这些决策都由基于分析和人工智能的预测模型提供支持。
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