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科技导报 |研究论文 2021 , 39 (15) : 135 -141
人工智能助力新冠肺炎疫情防控的实践情景
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沙德春, 荆晶
作者信息
    河南农业大学信息与管理科学学院, 郑州 450046
作者简介:
沙德春,副教授,研究方向为科技创新管理、科学计量学,电子信箱:shadechun8211@163.com
Practical scenarios of artificial intelligence in the prevention and control of COVID-19
  • SHA Dechun, JING Jing
  • Affiliations
      College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China
    出版时间: 2021-08-13 doi: 10.3981/j.issn.1000-7857.2021.15.014
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    分析了人工智能助力新冠肺炎疫情防控的实践情境,主要包括疫情监测预警、医疗诊断、病毒及药物研发等。人工智能技术的应用对控制疫情传播范围、缓解诊疗压力、提升研发效率等具有显著效果。根据人工智能助力疫情防控上面临的法规伦理、数据安全、算法偏见等现实难题,提出完善法律法规、保障数据安全、加强人才培养等发展建议。
    人工智能  /  新型冠状病毒肺炎  /  医疗
    In early 2020, COVID-19 outbroke in many countries around the world. Governments of various countries have since adopted diversified prevention and control measures to control the epidemic. Among them, AI has been an important auxiliary means that plays a unique role in prevention and control of COVID-19. The practical scenarios of AI assisting the prevention and control of COVID-19 have been focused on research field, mainly including epidemic monitoring and early warning, medical diagnosis, virus and drug research and development. The application of AI technology has significant effects on controlling the spread of the epidemic, alleviating the pressure of diagnosis and treatment and improving the efficiency of research and development. At the same time, AI is still facing practical problems such as regulations and ethics, data security, and algorithmic bias. Based on this, suggestions such as perfecting laws and regulations, ensuring data security, and strengthening talent training are proposed.
    artificial intelligence  /  COVID-19  /  medical
    沙德春, 荆晶. 人工智能助力新冠肺炎疫情防控的实践情景. 科技导报, 2021 , 39 (15) : 135 -141 . DOI: 10.3981/j.issn.1000-7857.2021.15.014
    SHA Dechun, JING Jing. Practical scenarios of artificial intelligence in the prevention and control of COVID-19[J]. Science & Technology Review, 2021 , 39 (15) : 135 -141 . DOI: 10.3981/j.issn.1000-7857.2021.15.014

      河南省高层次人才特殊支持中原千人计划项目(ZYQR201912202);河南省软科学研究项目(212400410087);河南省教育科学规划重点课题(2020-JKGHZD-15);河南省教育厅人文社会科学研究项目(2020-ZZJH-183)

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    doi: 10.3981/j.issn.1000-7857.2021.15.014
    • 接收时间:2020-06-09
    • 首发时间:2021-09-07
    • 出版时间:2021-08-13
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    • 收稿日期:2020-06-09
    • 修回日期:2021-03-21
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    2种不同金属材料的力学参数

    Family
    属数
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    种数
    Number of
    species
    占总种数比例
    Percentage of
    total species (%)

    Genus
    种数
    Number of
    species
    占总种数比例
    Percentage of total
    species (%)
    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
    光柄菇属 Pluteus 5 2.39
    红菇属 Russula 17 8.13
    栓菌属 Trametes 5 2.39
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