Survey of Artificial Intelligence in COVID-19 Pandemic

doi:10.3778/j.issn.1002-8331.2208-0229

Abstract

Abstract: The outbreak of novel coronavirus pneumonia（COVID-19） poses a great threat to the safety of human life and property in the world. Artificial intelligence（AI） has played an irreplaceable role in helping to win the battle against the epidemic. With the help of AI, the shortage of medical resources has been greatly alleviated, the efficiency of medical diagnosis has been improved, and the risk of contact infection has been avoided. Firstly, the background knowledge of COVID-19 and AI is expounded. Then, the research progress of AI in COVID-19 is discussed from the eight aspects of epidemic prevention and control, including epidemic trend prediction, epidemic traceability, detection and diagnosis, drug development, vaccine development, drug reuse, network public opinion control and genome sequencing, and the challenges faced by AI in the epidemic are listed. Then it discusses the impact of the epidemic on China’s AI industry and the dialectical relationship between the two. Finally, it summarizes the full text.

Key words: artificial intelligence, corona virus disease, epidemic prevention and control, deep learning

摘要： 新型冠状病毒肺炎（corona virus disease，COVID-19）的暴发对全球人类的生命财产安全造成了巨大威胁。人工智能（artificial intelligence，AI）为助力打赢这场疫情攻坚战发挥了不可替代的作用。由于AI的助力，医疗资源紧张的问题得到大幅度缓解，并提高了医疗诊断效率，同时也避免接触感染的风险。阐述了COVID-19和AI的背景知识，从疫情趋势预测、疫情溯源追踪、检测诊断、药物开发、疫苗研制、药物再利用、网络舆论管控以及基因组测序这8个疫情防控的环节讨论了AI在本次COVID-19中的研究进展，并列举本次疫情中AI所面临的挑战，浅谈本次疫情对我国AI产业影响以及两者的辩证关系，对全文进行总结。

关键词: 人工智能, 新型冠状病毒肺炎, 疫情防控, 深度学习

SUN Shukui, FAN Jing, LI Zhanwen, QU Jinshuai, LU Peidong. Survey of Artificial Intelligence in COVID-19 Pandemic[J]. Computer Engineering and Applications, 2023, 59(5): 28-39.

孙书魁, 范菁, 李占稳, 曲金帅, 路佩东. 人工智能在新型冠状病毒肺炎中的研究综述[J]. 计算机工程与应用, 2023, 59(5): 28-39.

References

[1] LIU Y，GAYLE A A，WILDER-SMITH A，et al.The reproductive number of COVID-19 is higher compared to SARS coronavirus[J].Journal of Travel Medicine，2020：1-4.
[2] ROBINSON P C，LIEW D F L，TANNER H L，et al.COVID-19 therapeutics：challenges and directions for the future[J].Proceedings of the National Academy of Sciences，2022，119（15）：e2119893119.
[3] CASCELLA M，RAJNIK M，ALEEM A，et al.Features，evaluation，and treatment of coronavirus（COVID-19）[J].Statpearls[internet]，2022：32150360.
[4] ZHANG K，LIU X，SHEN J，et al.Clinically applicable AI system for accurate diagnosis，quantitative measurements，and prognosis of COVID-19 pneumonia using computed tomography[J].Cell，2020，181（6）：1423-1433.
[5] SONG C Y，XU J，HE J Q，et al.Immune dysfunction following COVID-19，especially in severe patients[J].Scientific Reports，2020，10（1）：1-11.
[6] YASSINE H M，SHAH Z.How could artificial intelligence aid in the fight against coronavirus? An interview with Dr Hadi M Yassine and Dr Zubair Shah by Felicity Poole，Commissioning Editor[J].Expert Review of Anti-infective Therapy，2020，18（6）：493-497.
[7] KUMAR V，SINGH D，KAUR M，et al.Overview of current state of research on the application of artificial intelligence techniques for COVID-19[J].PeerJ Computer Science，2021，7：e564.
[8] JAMSHIDI M，LALBAKHSH A，TALLA J，et al.Artificial intelligence and COVID-19：deep learning approaches for diagnosis and treatment[J].IEEE Access，2020，8：109581-109595.
[9] 蔡晓琼，郭晶磊，黄继汉，等.人工智能技术在新型冠状病毒肺炎中的应用[J].中国医学物理学杂志，2021，38（7）：915-920.
CAI X Q，GUO J L，HUANG J H，et al.Advances in research on artificial intelligence technology in COVID-19[J].Chinese Journal of Medical Physics，2021，38（7）：915-920.
[10] WU D，WU T，LIU Q，et al.The SARS-CoV-2 outbreak：what we know[J].International Journal of Infectious Diseases，2020，94：44-48.
[11] TOBAIQY M，QASHQARY M，AL-DAHERY S，et al.Therapeutic management of patients with COVID-19：a systematic review[J].Infection Prevention in Practice，2020，2（3）：100061.
[12] GOODFELLOW I，BENGIO Y，COURVILLE A.Deep learning[M].[S.l.]：MIT Press，2016.
[13] DONG S，WANG P，ABBAS K.A survey on deep learning and its applications[J].Computer Science Review，2021，40：100379.
[14] BRAGAZZI N L，DAI H，DAMIANI G，et al.How big data and artificial intelligence can help better manage the COVID-19 pandemic[J].International Journal of Environmental Research and Public Health，2020，17（9）：3176.
[15] GUPTA R，SRIVASTAVA D，SAHU M，et al.Artificial intelligence to deep learning：machine intelligence approach for drug discovery[J].Molecular Diversity，2021，25（3）：1315-1360.
[16] ZHENG C，DENG X，FU Q，et al.Deep learning-based detection for COVID-19 from chest CT using weak label[J].MedRxiv，2020.
[17] HUANG T，CHU Y，SHAMS S，et al.Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates[J].Journal of Biomedi-cal Informatics，2021，119：103818.
[18] LIU X，XU X，LI G，et al.Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States[J].BMC Public Health，2021，21（1）：1-7.
[19] FRIEDMAN J，LIU P，TROEGER C E，et al.Predictive performance of international COVID-19 mortality forecasting models[J].Nature Communications，2021，12（1）：1-13.
[20] LI Y，JIA W，WANG J，et al.ALeRT-COVID：attentive lockdown-aware transfer learning for predicting COVID-19 pandemics in different countries[J].Journal of Healthcare Informatics Research，2021，5（1）：98-113.
[21] WANG J，TANG K，FENG K，et al.High temperature and high humidity reduce the transmission of COVID-19[J].SSRN Electronic Journal，2020，3551767：2020b.
[22] BRAUER M，ZHAO J T，BENNITT F B，et al.Global access to handwashing：implications for COVID-19 control in low-income countries[J].Environmental Health Perspectives，2020，128（5）：057005.
[23] ALZU’BI A，ALASAL S A，KHEIRALLAH K A，et al.COVID-19 simulation study—the effect of strict non-pharmaceutical interventions（NPIs） on controlling the spread of COVID-19[J].PeerJ，2021，9：e11172.
[24] ROCKETT R J，ARNOTT A，LAM C，et al.Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling[J].Nature Medicine，2020，26（9）：1398-1404.
[25] HSIANG S，ALLEN D，ANNAN-PHAN S，et al.Publisher correction：the effect of large-scale anti-contagion policies on the COVID-19 pandemic[J].Nature，2020，585（7824）：E7.
[26] PARBAT D，CHAKRABORTY M.A python based support vector regression model for prediction of COVID19 cases in India[J].Chaos，Solitons & Fractals，2020，138：109942.
[27] DONG E，DU H，GARDNER L.An interactive web-based dashboard to track COVID-19 in real time[J].The Lancet Infectious Diseases，2020，20（5）：533-534.
[28] KERMACK W O，MCKENDRICK A G.A contribution to the mathematical theory of epidemics[J].Proceedings of the Royal Society of London，Series A，1927，115（772）：700-721.
[29] HETHCOTE H W.The mathematics of infectious diseases[J].SIAM Review，2000，42（4）：599-653.
[30] ZHENG N，DU S，WANG J，et al.Predicting COVID-19 in China using hybrid AI model[J].IEEE Transactions on Cybernetics，2020，50（7）：2891-2904.
[31] PURKAYASTHA S，BHATTACHARYYA R，BHADURI R，et al.A comparison of five epidemiological models for transmission of SARS-CoV-2 in India[J].BMC Infectious Diseases，2021，21（1）：1-23.
[32] LALMUANAWMA S，HUSSAIN J，CHHAKCHHUAK L.Applications of machine learning and artificial intelligence for Covid-19（SARS-CoV-2） pandemic：a review[J].Chaos，Solitons & Fractals，2020，139：110059.
[33] RAO A S R S，VAZQUEZ J A.Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine[J].Infection Control & Hospital Epidemiology，2020，41（7）：826-830.
[34] KUMAR A，GUPTA P K，SRIVASTAVA A.A review of modern technologies for tackling COVID-19 pandemic[J].Diabetes & Metabolic Syndrome：Clinical Research & Reviews，2020，14（4）：569-573.
[35] 刘思远，张丽军，刘雷.人工智能在抗击新型冠状病毒肺炎疫情中的应用[J].中国医学物理学杂志，2020，37（8）：1076-1080.
LIU S Y，ZHANG L J，LIU L.Application of artificial intelligence in fighting against COVID-19 pandemic[J].Chinese Journal of Medical Physics，2020，37（8）：1076-1080.
[36] FANG Y，ZHANG H，XIE J，et al.Sensitivity of chest CT for COVID-19：comparison to RT-PCR[J].Radiology，2020，296（2）：115-117.
[37] 刘锐，丁辉，尚媛园，等.COVID-19医学影像数据集及研究进展[J].计算机工程与应用，2021，57（22）：15-27.
LIU R，DING H，SHANG Y Y，et al.COVID-19 medical imaging dataset and research progress[J].Computer Engineering and Applications，2021，57（22）：15-27.
[38] PENG Y，LIU E，PENG S，et al.Using artificial intelligence technology to fight COVID-19：a review[J].Artificial Intelligence Review，2022：1-37.
[39] YASAKA K，AKAI H，KUNIMATSU A，et al.Deep learning with convolutional neural network in radiology[J].Japanese Journal of Radiology，2018，36（4）：257-272.
[40] ABBASIAN ARDAKANI A，ACHARYA U R，HABIBOLLAHI S，et al.COVIDiag：a clinical CAD system to diagnose COVID-19 pneumonia based on CT findings[J].European Radiology，2021，31（1）：121-130.
[41] BAI H X，WANG R，XIONG Z，et al.Erratum：artificial intelligence augmentation of radiologist performance in distinguishing COVID-19 from pneumonia of other origin at chest CT（Radiology（2020） 2963（E156-E165））[J].Radiology，2021：225.
[42] ARDAKANI A A，KANAFI A R，ACHARYA U R，et al.Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images：results of 10 convolutional neural networks[J].Computers in Biology and Medicine，2020，121：103795.
[43] HAN Z，WEI B，HONG Y，et al.Accurate screening of COVID-19 using attention-based deep 3D multiple instance learning[J].IEEE Transactions on Medical Imaging，2020，39（8）：2584-2594.
[44] KO H，CHUNG H，KANG W S，et al.COVID-19 pneumonia diagnosis using a simple 2D deep learning framework with a single chest CT image：model develop-ment and validation[J].Journal of Medical Internet Research，2020，22（6）：e19569.
[45] LI L，QIN L，XU Z，et al.Using artificial intelligence to detect COVID-19 and community-acquired pneumonia based on pulmonary CT：evaluation of the diagnostic accuracy[J].Radiology，2020，296（2）：E65-E71.
[46] LIU C，WANG X，LIU C，et al.Differentiating novel coronavirus pneumonia from general pneumonia based on machine learning[J].Biomedical Engineering Online，2020，19（1）：1-14.
[47] MEI X，LEE H C，DIAO K，et al.Artificial intelligence-enabled rapid diagnosis of patients with COVID-19[J].Nature Medicine，2020，26（8）：1224-1228.
[48] MISHRA A K，DAS S K，ROY P，et al.Identifying COVID19 from chest CT images：a deep convolutional neural networks based approach[J].Journal of Healthcare Engineering，2020：8843664.
[49] 谢娟英，张凯云.XR-MSF-Unet：新冠肺炎肺部CT图像自动分割模型[J].计算机科学与探索，2022，16（8）：1850-1864.
XIE J Y，ZHANG K Y.XR-MSF-Unet：an automatic segmentation model for COVID-19 lung CT images[J].Journal of Frontiers of Computer Science and Technology，2022，16（8）：1850-1864.
[50] NI Q，SUN Z Y，QI L，et al.A deep learning approach to characterize 2019 coronavirus disease（COVID-19） pneumonia in chest CT images[J].European Radiology，2020，30（12）：6517-6527.
[51] 王威，胡亿洋，王新，等.针对新型冠状病毒肺炎X射线图像识别的DD-CovidNet模型[J].计算机辅助设计与图形学学报，2021，33（11）：1649-1657.
WANG W，HU Y Y，WANG X，et al.DD-CovidNet model for X-ray images recognition of coronavirus disease 2019[J].Journal of Computer-Aided Design & Computer Graphics，2021，33（11）：1649-1657.
[52] STEPHEN O，SAIN M，MADUH U J，et al.An efficient deep learning approach to pneumonia classification in healthcare[J].Journal of Healthcare Engineering，2019：4180949.
[53] TO?A?AR M，ERGEN B，C?MERT Z.COVID-19 detection using deep learning models to exploit social mimic optimization and structured chest X-ray images using fuzzy color and stacking approaches[J].Computers in Biology and Medicine，2020，121：103805.
[54] TUNCER T，DOGAN S，OZYURT F.An automated residual exemplar local binary pattern and iterative ReliefF based COVID-19 detection method using chest X-ray image[J].Chemometrics and Intelligent Laboratory Systems，2020，203：104054.
[55] UCAR F，KORKMAZ D.COVIDiagnosis-Net：deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019（COVID-19） from X-ray images[J].Medical Hypotheses，2020，140：109761.
[56] KHAN A I，SHAH J L，BHAT M M.CoroNet：a deep neural network for detection and diagnosis of COVID-19 from chest X-ray images[J].Computer Methods and Programs in Biomedicine，2020，196：105581.
[57] RAHIMZADEH M，ATTAR A.A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2[J].Informatics in Medicine Unlocked，2020，19：100360.
[58] OZTURK T，TALO M，YILDIRIM E A，et al.Automated detection of COVID-19 cases using deep neural networks with X-ray images[J].Computers in Biology and Medicine，2020，121：103792.
[59] BRUNESE L，MERCALDO F，REGINELLI A，et al.Explainable deep learning for pulmonary disease and coronavirus COVID-19 detection from X-rays[J].Computer Methods and Programs in Biomedicine，2020，196：105608.
[60] LOEY M，SMARANDACHE F，KHALIFA N E M.Within the lack of chest COVID-19 X-ray dataset：a novel detection model based on GAN and deep transfer learning[J].Symmetry，2020，12（4）：651.
[61] ZHAVORONKOV A.Artificial intelligence for drug discovery，biomarker development，and generation of novel chemistry[J].Molecular Pharmaceutics，2018，15（10）：4311-4313.
[62] 茅鸯对，柳鹏程.药物研发领域人工智能应用与创新发展策略探讨[J].中国新药与临床杂志，2021，40（6）：430-435.
MAO Y D，LIU P C.Discussion on application and innovative development strategy of artificial intelligence in drug research and development field[J].Chinese Journal of New Drugs and Clinical Remdeies，2021，40（6）：430-435.
[63] HASSANZADEH P，ATYABI F，DINARVAND R.The significance of artificial intelligence in drug delivery system design[J].Advanced Drug Delivery Reviews，2019，151：169-190.
[64] JOSHI Tanuja，JOSHI Tushar，PUNDIR H，et al.Predictive modeling by deep learning，virtual screening and molecular dynamics study of natural compounds against SARS-CoV-2 main protease[J].Journal of Biomolecular Structure and Dynamics，2021，39（17）：6728-6746.
[65] TON A T，GENTILE F，HSING M，et al.Rapid identification of potential inhibitors of SARS‐CoV‐2 main protease by deep docking of 1.3 billion compounds[J].Molecular Informatics，2020，39（8）：2000028.
[66] RUSSO G，RECHE P，PENNISI M，et al.The combination of artificial intelligence and systems biology for intelligent vaccine design[J].Expert Opinion on Drug Discovery，2020，15（11）：1267-1281.
[67] ANASIR M I，POH C L.Structural vaccinology for viral vaccine design[J].Frontiers in Microbiology，2019，10：738.
[68] 李兴航，杨晓明.抗原设计新技术及其在疫苗中的应用和发展[J].中国生物制品学杂志，2021，34（4）：468-474.
LI X H，YANG X M.New technology for antigen design and its application in vaccine[J].Chinese Journal of Biologicals，2021，34（4）：468-474.
[69] ONG E，WONG M U，HUFFMAN A，et al.COVID-19 coronavirus vaccine design using reverse vaccinology and machine learning[J].Frontiers in Immunology，2020，11：1581.
[70] 王晓旭，吴心怡，梁浩，等.新型冠状病毒肺炎治疗药物研发进展[J].中国药理学与毒理学杂志，2021，35（8）：561-574.
WANG X X，WU X Y，LIANG H，et al.Progress in drug development for treatment of COVID-19[J].Chinese Journal of Pharmacology and Toxicology，2021，35（8）：561-574.
[71] OZERY-FLATO M，GOLDSCHMIDT Y，SHAHAM O，et al.Framework for identifying drug repurposing candidates from observational healthcare data[J].Jamia Open，2020，3（4）：536-544.
[72] PARANJPE M D，TAUBES A，SIROTA M.Insights into computational drug repurposing for neurodegenerative disease[J].Trends in Pharmacological Sciences，2019，40（8）：565-576.
[73] 陈杨，陈轶伦，曾文杰，等.人工智能在药物再定位的应用[J].中国医药导刊，2022，24（4）：334-341.
CHEN Y，CHEN Y L，ZENG W J，et al.Application of artificial intelligence in drug repurposing[J].Chinese Journal of Medicinal Guide，2022，24（4）：334-341.
[74] ZHOU Y，HOU Y，SHEN J，et al.Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2[J].Cell Discovery，2020，6（1）：1-18.
[75] ZENG X，SONG X，MA T，et al.Repurpose open data to discover therapeutics for COVID-19 using deep learning[J].Journal of Proteome Research，2020，19（11）：4624-4636.
[76] MORSELLI GYSI D，DO VALLE í，ZITNIK M，et al.Network medicine framework for identifying drug-repurposing opportunities for COVID-19[J].Proceedings of the National Academy of Sciences，2021，118（19）：e2025581118.
[77] WANG Q，LI M，WANG X，et al.COVID-19 literature knowledge graph construction and drug repurposing report generation[J].arXiv：2007.00576，2020.
[78] ZHANG R，HRISTOVSKI D，SCHUTTE D，et al.Drug repurposing for COVID-19 via knowledge graph completion[J].Journal of Biomedical Informatics，2021，115：103696.
[79] GORDON D E，JANG G M，BOUHADDOU M，et al.A SARS-CoV-2 protein interaction map reveals targets for drug repurposing[J].Nature，2020，583（7816）：459-468.
[80] BECK B R，SHIN B，CHOI Y，et al.Predicting commercially available antiviral drugs that may act on the novel coronavirus（SARS-CoV-2） through a drug-target interaction deep learning model[J].Computational and Structural Biotechnology Journal，2020，18：784-790.
[81] MALL R，ELBASIR A，AL MEER H，et al.Data-driven drug repurposing for COVID-19[J].ChemRxiv，2020.
[82] KHAN R，SHRIVASTAVA P，KAPOOR A，et al.Social media analysis with AI：sentiment analysis techniques for the analysis of twitter covid-19 data[J].Critical Rev，2020，7（9）：2761-2774.
[83] 陈慧敏，金思辰，林微，等.新冠疫情相关社交媒体谣言传播量化分析[J].计算机研究与发展，2021，58（7）：1366-1384.
CHEN H M，JIN S C，LIN W，et al.Quantitative analysis on the communication of COVID-19 related social media rumors[J].Journal of Computer Research and Development，2021，58（7）：1366-1384.
[84] SAMUEL J，ALI G G，RAHMAN M，et al.COVID-19 public sentiment insights and machine learning for tweets classification[J].Information，2020，11（6）：314.
[85] NAWAZ M S，FOURNIER-VIGER P，SHOJAEE A，et al.Using artificial intelligence techniques for COVID-19 genome analysis[J].Applied Intelligence，2021，51（5）：3086-3103.
[86] WANG S，KANG B，MA J，et al.A deep learning algorithm using CT images to screen for Corona Virus Disease（COVID-19）[J].European Radiology，2021，31（8）：6096-6104.
[87] ?ZKAYA U，?ZTüRK ?，BARSTUGAN M.Coronavirus（COVID-19） classification using deep features fusion and ranking technique[M]//Big data analytics and artificial intelligence against COVID-19：innovation vision and approach.Cham：Springer，2020：281-295.
[88] PHAM Q V，NGUYEN D C，HUYNH-THE T，et al.Artificial intelligence（AI） and big data for coronavirus（COVID-19） pandemic：a survey on the state-of-the-arts[J].IEEE Access，2020，8：130820.
[89] LIU W，LIANG Y，BAO X，et al.China’s logistics development trends in the post COVID-19 era[J].International Journal of Logistics Research and Applications，2022，25（6）：965-976.
[90] PERKUMIENĖ D，OSAMEDE A，ANDRIUKAITIEN? R，et al.The impact of COVID-19 on the transportation and logistics industry[J].Problems and Perspectives in Management，2021，19（4）：458-469.
[91] SERANMADEVI R，CHAKRAVERTY S，RAJ B，et al.Utilisation of virtual assistant and its impact on retail industry[C]//2022 6th International Conference on Intelligent Computing and Control Systems（ICICCS），2022：1729-1733.
[92] HAR L L，RASHID U K，TE CHUAN L，et al.Revolution of retail industry：from perspective of retail 1.0 to 4.0[J].Procedia Computer Science，2022，200：1615-1625.
[93] YANG T，YI X，LU S，et al.Intelligent manufacturing for the process industry driven by industrial artificial intelligence[J].Engineering，2021，7（9）：1224-1230.
[94] ANWARSHA A，BABU T N.Artificial intelligence-based fault diagnosis procedure for a sustainable manufacturing industry[C]//IOP Conference Series：Earth and Environmental Science，2022，1055（1）：012012.
[95] FU Y.Research on the development trend of online education industry considering the influence of big data and artificial intelligence[C]//The International Conference on Cyber Security Intelligence and Analytics.Cham：Springer，2019：852-859.
[96] CHEN L，CHEN P，LIN Z.Artificial intelligence in education：a review[J].IEEE Access，2020，8：75264-75278.