Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China

被引:43
作者
Dong, Jiancheng [1 ,2 ]
Wu, Huiqun [2 ]
Zhou, Dong [2 ]
Li, Kaixiang [1 ]
Zhang, Yuanpeng [2 ,3 ]
Ji, Hanzhen [4 ]
Tong, Zhuang [1 ]
Lou, Shuai [5 ]
Liu, Zhangsuo [1 ]
机构
[1] Zhengzhou Univ, Affiliated Hosp 1, Med Big Data Res Ctr, Zhengzhou, Peoples R China
[2] Nantong Univ, Med Sch, Dept Med Informat, Nantong, Peoples R China
[3] Hong Kong Polytech Univ, Dept Hlth Technol & Informat, Hong Kong, Peoples R China
[4] Nantong Univ, Affiliated Hosp 3, Nantong, Peoples R China
[5] Jiangsu Zhongkang Software Co Ltd, Nantong, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Big data; Artificial intelligence; COVID-19; Deep learning; Epidemic prevention and control; DATA ANALYTICS; MEDICINE; SYSTEM; CHALLENGES; EPIDEMIC; NETWORK;
D O I
10.1007/s10916-021-01757-0
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on the control of infection sources, interruption of transmission channels and vaccine development. Big data and AI are effective technologies to identify the source of infection and have an irreplaceable role in distinguishing close contacts and suspicious populations. Advanced computational analysis is beneficial to accelerate the speed of vaccine research and development and to improve the quality of vaccines. AI provides support in automatically processing relevant data from medical images and clinical features, tests and examination findings; predicting disease progression and prognosis; and even recommending treatment plans and strategies. This paper reviews the application of big data and AI in the COVID-19 prevention, diagnosis, treatment and management decisions in China to explain how to apply big data and AI technology to address the common problems in the COVID-19 pandemic. Although the findings regarding the application of big data and AI technologies in sudden public health events lack validation of repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.
引用
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页数:11
相关论文
共 129 条
[1]   Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing [J].
Agbehadji, Israel Edem ;
Awuzie, Bankole Osita ;
Ngowi, Alfred Beati ;
Millham, Richard C. .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (15) :1-16
[2]   Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies [J].
Ahmed, Syed Faraz ;
Quadeer, Ahmed A. ;
McKay, Matthew R. .
VIRUSES-BASEL, 2020, 12 (03)
[3]   Artificial intelligence and COVID-19: A multidisciplinary approach [J].
Ahuja, Abhimanyu S. ;
Reddy, Vineet Pasam ;
Marques, Oge .
INTEGRATIVE MEDICINE RESEARCH, 2020, 9 (03)
[4]  
[Anonymous], 2020, LANCET, V395, P1230, DOI 10.1016/S0140-6736(20)30864-3
[5]  
[Anonymous], 2020, J INFECTION, DOI [DOI 10.1183/13993003.00547-2020, DOI 10.1007/s12083-021-01087-5]
[6]  
[Anonymous], 2020, TODAY SCI TECHNOLOGY, V3, P44
[7]   Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis [J].
Ao, Chunyan ;
Jin, Shunshan ;
Ding, Hui ;
Zou, Quan ;
Yu, Liang .
CURRENT PHARMACEUTICAL DESIGN, 2020, 26 (26) :3069-3075
[8]   Artificial intelligence in cancer imaging: Clinical challenges and applications [J].
Bi, Wenya Linda ;
Hosny, Ahmed ;
Schabath, Matthew B. ;
Giger, Maryellen L. ;
Birkbak, Nicolai J. ;
Mehrtash, Alireza ;
Allison, Tavis ;
Arnaout, Omar ;
Abbosh, Christopher ;
Dunn, Ian F. ;
Mak, Raymond H. ;
Tamimi, Rulla M. ;
Tempany, Clare M. ;
Swanton, Charles ;
Hoffmann, Udo ;
Schwartz, Lawrence H. ;
Gillies, Robert J. ;
Huang, Raymond Y. ;
Aerts, Hugo J. W. L. .
CA-A CANCER JOURNAL FOR CLINICIANS, 2019, 69 (02) :127-157
[9]   The important role of polysaccharides from a traditional Chinese medicine-Lung Cleansing and Detoxifying Decoction against the COVID-19 pandemic [J].
Cao, Peng ;
Wu, Sanlan ;
Wu, Tingting ;
Deng, Yahui ;
Zhang, Qilin ;
Wang, Kaiping ;
Zhang, Yu .
CARBOHYDRATE POLYMERS, 2020, 240
[10]   Deep Learning in Medical Image Analysis [J].
Chan, Heang-Ping ;
Samala, Ravi K. ;
Hadjiiski, Lubomir M. ;
Zhou, Chuan .
DEEP LEARNING IN MEDICAL IMAGE ANALYSIS: CHALLENGES AND APPLICATIONS, 2020, 1213 :3-21