{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T12:26:31Z","timestamp":1777983991135,"version":"3.51.4"},"reference-count":243,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-009"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-001"}],"funder":[{"name":"David MacKay Newton"},{"DOI":"10.13039\/100012338","name":"Alan Turing Institute","doi-asserted-by":"publisher","award":["EP\/N510129\/1"],"award-info":[{"award-number":["EP\/N510129\/1"]}],"id":[{"id":"10.13039\/100012338","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012338","name":"Alan Turing Institute","doi-asserted-by":"publisher","award":["U\/B\/000074"],"award-info":[{"award-number":["U\/B\/000074"]}],"id":[{"id":"10.13039\/100012338","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000275","name":"Leverhulme Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000275","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ARC","award":["DE170100128"],"award-info":[{"award-number":["DE170100128"]}]},{"name":"ARC","award":["DP200100757"],"award-info":[{"award-number":["DP200100757"]}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["APP1194910"],"award-info":[{"award-number":["APP1194910"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["088130\/Z\/09\/Z"],"award-info":[{"award-number":["088130\/Z\/09\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/P025374\/1"],"award-info":[{"award-number":["EP\/P025374\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/S033564\/1"],"award-info":[{"award-number":["EP\/S033564\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Artif. Intell."],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1109\/tai.2020.3020521","type":"journal-article","created":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T15:46:37Z","timestamp":1625067997000},"page":"85-103","source":"Crossref","is-referenced-by-count":157,"title":["Leveraging Data Science to Combat COVID-19: A Comprehensive Review"],"prefix":"10.1109","volume":"1","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5662-4777","authenticated-orcid":false,"given":"Siddique","family":"Latif","sequence":"first","affiliation":[{"name":"University of Southern Queensland, Springfield, Queensland, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7278-8488","authenticated-orcid":false,"given":"Muhammad","family":"Usman","sequence":"additional","affiliation":[{"name":"Seoul National University, Seoul, South Korea"}]},{"given":"Sanaullah","family":"Manzoor","sequence":"additional","affiliation":[{"name":"Center for Artificial Intelligence in Medicine and Imaging, HealthHub Company Ltd., Seoul, South Korea"}]},{"given":"Waleed","family":"Iqbal","sequence":"additional","affiliation":[{"name":"Information Technology University, Punjab, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9466-2475","authenticated-orcid":false,"given":"Junaid","family":"Qadir","sequence":"additional","affiliation":[{"name":"Alan Turing Institute, London, U.K."}]},{"given":"Gareth","family":"Tyson","sequence":"additional","affiliation":[{"name":"Queen Mary University of London, London, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7739-6184","authenticated-orcid":false,"given":"Ignacio","family":"Castro","sequence":"additional","affiliation":[{"name":"Information Technology University, Punjab, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0779-9439","authenticated-orcid":false,"given":"Adeel","family":"Razi","sequence":"additional","affiliation":[{"name":"Alan Turing Institute, London, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2400-6303","authenticated-orcid":false,"given":"Maged N. Kamel","family":"Boulos","sequence":"additional","affiliation":[{"name":"Turner Institute for Brain and Mental Health & Monash Biomedical Imaging, Monash University, Melbourne, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1915-7158","authenticated-orcid":false,"given":"Adrian","family":"Weller","sequence":"additional","affiliation":[{"name":"the School of Information Management, Sun Yat-sen University, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7013-0121","authenticated-orcid":false,"given":"Jon","family":"Crowcroft","sequence":"additional","affiliation":[{"name":"Alan Turing Institute, London, U.K."}]}],"member":"263","reference":[{"key":"ref170","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.m1373"},{"key":"ref172","article-title":"Tracesecure: Towards privacy preserving contact tracing","author":"bell","year":"2020"},{"key":"ref171","article-title":"Dp-3t documentation","year":"0"},{"key":"ref174","article-title":"Computational predictions of protein structures associated with COVID-19","author":"john","year":"2020"},{"key":"ref173","article-title":"Assessing disease exposure risk with location histories and protecting privacy: A cryptographic approach in response to a global pandemic","author":"berke","year":"2020","journal-title":"arXiv 2003 14412"},{"key":"ref176","article-title":"De novo design of new chemical entities (NCEs) for SARS-CoV-2 using artificial intelligence","author":"bung","year":"0"},{"key":"ref175","doi-asserted-by":"publisher","DOI":"10.1002\/prot.25834"},{"key":"ref178","article-title":"Prediction of potential commercially inhibitors against SARS-CoV-2 by multi-task deep model","author":"hu","year":"2020","journal-title":"arXiv 2003 00728"},{"key":"ref177","article-title":"CRISPR-based surveillance for COVID-19 using genomically-comprehensive machine learning design","author":"metsky","year":"2020","journal-title":"BioRxiv"},{"key":"ref168","author":"cohen","year":"0"},{"key":"ref169","article-title":"Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs","author":"cho","year":"2020","journal-title":"arXiv 2003 11511"},{"key":"ref39","article-title":"Coronavirus on social media: Analyzing misinformation in Twitter conversations","author":"sharma","year":"2020","journal-title":"arXiv 2003 12309"},{"key":"ref38","first-page":"599","article-title":"Flu detector-tracking epidemics on Twitter","author":"lampos","year":"2010","journal-title":"Proc Eur Conf Mach Learn Knowl Discovery Databases"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(01)00702-0"},{"key":"ref32","article-title":"Causal explanations, error rates, and human judgment biases missing from the covid-19 narrative and statistics","author":"fenton","year":"0"},{"key":"ref31","article-title":"Understanding the covid19 outbreak: A comparative data analytics and study","author":"koubaa","year":"2020","journal-title":"arXiv 2003 14150"},{"key":"ref30","article-title":"Coronasurveys: Monitoring COVID-19 incidence via open polls","author":"b","year":"2020"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1964858.1964874"},{"key":"ref36","first-page":"1568","article-title":"Twitter catches the flu: Detecting influenza epidemics using Twitter","author":"aramaki","year":"0","journal-title":"Proc Conf Empirical Methods Natural Lang Process"},{"key":"ref35","article-title":"Coronada","author":"jacobs","year":"2020"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref181","author":"boucher","year":"0"},{"key":"ref180","article-title":"AI-aided design of novel targeted covalent inhibitors against SARS-CoV-2","author":"tang","year":"2020","journal-title":"BioRxiv"},{"key":"ref185","article-title":"Coronavirus (covid-19) classification using ct images by machine learning methods","author":"barstugan","year":"2020","journal-title":"arXiv 2003 09424"},{"key":"ref184","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.00775-2020"},{"key":"ref183","article-title":"Covid-19 screening on chest x-ray images using deep learning based anomaly detection","author":"zhang","year":"2020","journal-title":"arXiv 2003 12338"},{"key":"ref182","article-title":"Lung infection quantification of COVID-19 in ct images with deep learning","author":"shan","year":"2020","journal-title":"arXiv 2003 04655"},{"key":"ref189","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics10060358"},{"key":"ref188","article-title":"Classification of COVID-19 in chest x-ray images using DeTraC deep convolutional neural network","author":"abbas","year":"2020","journal-title":"arXiv 2003 13815"},{"key":"ref187","article-title":"Automated methods for detection and classification pneumonia based on x-ray images using deep learning","author":"asnaoui","year":"2020","journal-title":"arXiv 2003 14363"},{"key":"ref186","article-title":"Coronavirus detection and analysis on chest ct with deep learning","author":"gozes","year":"2020","journal-title":"arXiv 2004 02640"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1002\/pro.3730"},{"key":"ref27","article-title":"COVID-19: The first public Coronavirus Twitter dataset","author":"chen","year":"2020","journal-title":"arXiv 2003 07372"},{"key":"ref179","doi-asserted-by":"publisher","DOI":"10.1007\/s12539-020-00376-6"},{"key":"ref29","article-title":"Dataset of infections in germany","year":"2020"},{"key":"ref20","article-title":"CSSEGISandData\/COVID-19","year":"2020"},{"key":"ref22","article-title":"LitCovid","year":"2020"},{"key":"ref21","article-title":"U.S. Health Weather Map","year":"2020"},{"key":"ref24","article-title":"ncov2019 epidemiological data","year":"2020"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1038\/d41586-020-00694-1","article-title":"Keep up with the latest coronavirus research","volume":"579","author":"chen","year":"2020","journal-title":"Nature"},{"key":"ref26","article-title":"New york times dataset","year":"2020"},{"key":"ref25","article-title":"Novel corona-virus dataset","year":"2020"},{"key":"ref50","article-title":"Covid-19 x rays","year":"2020"},{"key":"ref51","article-title":"COVID-CT-Dataset: A CT scan dataset about COVID-19","author":"zhao","year":"2020","journal-title":"arXiv 2003 13865"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2015.7280317"},{"key":"ref153","article-title":"Covid-19 and computer audition: An overview on what speech & sound analysis could contribute in the SARS-CoV-2 Corona crisis","author":"schuller","year":"2020","journal-title":"arXiv 2003 11117"},{"key":"ref156","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2017.8273622"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.1111\/ecc.13033"},{"key":"ref150","doi-asserted-by":"crossref","DOI":"10.20944\/preprints202003.0286.v1","article-title":"Network bioinformatics analysis provides insight into drug repurposing for COVID-2019","author":"li","year":"2020"},{"key":"ref152","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.03.012"},{"key":"ref151","article-title":"Current status of global research on novel Coronavirus disease (COVID-19) : A bibliometric analysis and knowledge mapping","author":"hossain","year":"2020","journal-title":"Available at SSRN"},{"key":"ref146","article-title":"What is the people posting about symptoms related to Coronavirus in Bogota, Colombia","author":"saire","year":"2020","journal-title":"arXiv 2003 11159"},{"key":"ref147","article-title":"‘go eat a bat, chang!’: An early look on the emergence of Sinophobic behavior on web communities in the face of COVID-19","author":"schild","year":"2020"},{"key":"ref148","article-title":"The COVID-19 social media infodemic","author":"cinelli","year":"2020","journal-title":"arXiv 2003 05004"},{"key":"ref149","article-title":"A first look at COVID-19 information and misinformation sharing on Twitter","author":"singh","year":"2020","journal-title":"arXiv 2003 13907"},{"key":"ref59","article-title":"Pakistan coronavirus citywise data","author":"usmani","year":"2020"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2020.138959"},{"key":"ref57","first-page":"1e","article-title":"Potential COVID-2019 3c-like protease inhibitors designed using generative deep learning approaches","volume":"307","author":"zhavoronkov","year":"2020","journal-title":"Insilico Med Hong Kong Ltd A"},{"key":"ref56","article-title":"Cov-clear | citizen science to help track and clear covid","year":"2020"},{"key":"ref55","article-title":"Let's beat covid-19 - take the survey to help one million doctors","year":"2020"},{"key":"ref54","article-title":"Covid19 impact survey","year":"2020"},{"key":"ref53","article-title":"Covid-19 x rays","year":"2020"},{"key":"ref52","article-title":"Mosmeddata: Chest ct scans with covid-19 related findings","author":"morozov","year":"2020","journal-title":"arXiv 2005 06465"},{"key":"ref40","article-title":"A first instagram dataset on covid-19","author":"zarei","year":"2020","journal-title":"arXiv 2004 12226"},{"key":"ref167","year":"0","journal-title":"TraceTogether - Behind the Scenes Look at its Development Process"},{"key":"ref166","author":"ye","year":"0"},{"key":"ref165","article-title":"Geographical tracking and mapping of coronavirus disease COVID-19\/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics","volume":"19","author":"boulos","year":"2020","journal-title":"International Journal of Health Geographics"},{"key":"ref164","article-title":"Poland: App helps police monitor home quarantine","year":"0"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.1109\/IRI49571.2020.00033"},{"key":"ref162","year":"0","journal-title":"The Verge"},{"key":"ref161","article-title":"$\\alpha$-satellite: An AI-driven system and benchmark datasets for hierarchical community-level risk assessment to help combat COVID-19","author":"ye","year":"2020","journal-title":"arXiv 2003 12232"},{"key":"ref160","doi-asserted-by":"crossref","first-page":"93?117","DOI":"10.3390\/fi9040093","article-title":"How 5g wireless (and concomitant technologies) will revolutionize healthcare","volume":"9","author":"latif","year":"2017","journal-title":"Future Internet"},{"key":"ref4","author":"hao","year":"0","journal-title":"Over 24 000 Coronavirus Research Papers are now Available in one Place"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1056\/NEJMoa2001017","article-title":"A novel coronavirus from patients with pneumonia in China, 2019","volume":"382","author":"zhu","year":"2020","journal-title":"New England J Medicine"},{"key":"ref6","author":"schaar","year":"0","journal-title":"How Artificial Intelligence Machine Learn Can Help Healthcare Syst Respond to COVID-19"},{"key":"ref5","article-title":"Mapping the landscape of artificial intelligence applications against COVID-19","author":"bullock","year":"2020","journal-title":"arXiv 2003 11336"},{"key":"ref8","article-title":"COVID-19 image data collection","author":"cohen","year":"2020"},{"key":"ref159","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2020.100378"},{"key":"ref7","article-title":"Covid-19-BSTI Imaging Database","year":"2020"},{"key":"ref49","article-title":"COVID Chest-Xray Dataset","year":"2020"},{"key":"ref157","doi-asserted-by":"publisher","DOI":"10.1109\/I2MTC.2012.6229523"},{"key":"ref9","article-title":"COVID-19 CT segmentation dataset","year":"2020"},{"key":"ref158","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2014.6943870"},{"key":"ref46","article-title":"Wikipedia database downloaod","year":"2020"},{"key":"ref45","article-title":"bioRXiv, accessed on: 12-April-2020","year":"0"},{"key":"ref48","first-page":"978","volume":"10","author":"mery","year":"2015","journal-title":"Computer Vision for X-ray Testing"},{"key":"ref47","article-title":"COVID-Net: A tailored deep convolutional neural network design for detection of COVID-19 cases from chest radiography images","author":"wang","year":"2020","journal-title":"arXiv 2003 09871"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2926732"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/ciaa247"},{"key":"ref44","article-title":"medRxiv, accessed on: 12-April-2020","year":"0"},{"key":"ref43","article-title":"arXiv, accessed on: 12-April-2020","year":"0"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1080\/17477778.2020.1751570"},{"key":"ref72","year":"2020","journal-title":"Startup Uses Fever Detection Technology To Stop Spread of Coronavirus"},{"key":"ref71","doi-asserted-by":"crossref","first-page":"261","DOI":"10.4018\/978-1-5225-5270-3.ch011","article-title":"Mobile technologies for managing non-communicable diseases in developing countries","author":"latif","year":"2018","journal-title":"Mobile Applications and Solutions for Social Inclusion"},{"key":"ref70","first-page":"a14\ufffd100","article-title":"Artificial intelligence based clinical risk assessment in predicting cardiac related chest pain in patients presenting to emergency room","volume":"140","author":"wattanakit","year":"2019","journal-title":"Circulation"},{"key":"ref76","article-title":"Dynamic causal modelling of COVID-19","volume":"5","author":"friston","year":"2020"},{"key":"ref77","article-title":"Inferring COVID-19 spreading rates and potential change points for case number forecasts","author":"dehning","year":"2020"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1927.0118"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(20)30144-4"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.12688\/wellcomeopenres.15986.1"},{"key":"ref79","author":"tufekci","year":"2020","journal-title":"Don’t Believe the COVID-19 Models That's not What they’re for"},{"key":"ref60","article-title":"Uncover covid19 challenge","year":"2020"},{"key":"ref62","article-title":"Chemml: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data","author":"haghighatlari","year":"2019","journal-title":"Wiley Interdisciplinary Reviews: Computational Molecular Science"},{"key":"ref61","article-title":"Covid19 global forecasting challenge, the white house office of science and technology","year":"2020"},{"key":"ref63","doi-asserted-by":"crossref","DOI":"10.31223\/OSF.IO\/NHGJ3","article-title":"Early evidence that COVID-19 government policies reduce urban air pollution","author":"cadotte","year":"2020"},{"key":"ref64","article-title":"World's air pollution: Real-time air quality index","year":"2020"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abc0764"},{"key":"ref66","article-title":"Data world","year":"0"},{"key":"ref67","article-title":"Time course quantitative detection of sars-cov-2 in parisian wastewaters correlates with covid-19 confirmed cases","author":"wurtzer","year":"2020","journal-title":"medRxiv"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/S2352-3026(18)30118-2"},{"key":"ref69","first-page":"144","article-title":"Predicting diabetic neuropathy risk level using artificial neural network based on clinical characteristics of subjects with diabetes","volume":"36","author":"dave","year":"2019","journal-title":"Diabetic Med"},{"key":"ref197","article-title":"Using Twitter and web news mining to predict COVID-19 outbreak","author":"jahanbin","year":"2020"},{"key":"ref198","article-title":"Chinese public attention to COVID-19 epidemic: Based on social media","author":"zhao","year":"2020","journal-title":"medRxiv"},{"key":"ref199","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.2980007"},{"key":"ref193","article-title":"Covid-19 detection using artificial intelligence","author":"salman","year":"2020"},{"key":"ref194","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8296389"},{"key":"ref195","article-title":"Deepcovidexplainer: Explainable covid-19 predictions based on chest x-ray images","author":"karim","year":"2020","journal-title":"arXiv 2004 04582"},{"key":"ref196","doi-asserted-by":"publisher","DOI":"10.1007\/s13246-020-00865-4"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0019467"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.e2353"},{"key":"ref190","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2993291"},{"key":"ref93","article-title":"A simplified model for expected development of the SARS-CoV-2 (corona) spread in germany and us after social distancing","author":"schmitt","year":"2020","journal-title":"arXiv 2003 10891"},{"key":"ref191","article-title":"COVID-2019 detection using x-ray images and artificial intelligence hybrid systems","author":"alqudah","year":"0"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1093\/jtm\/taaa020"},{"key":"ref192","article-title":"Estimating uncertainty and interpretability in deep learning for Coronavirus (COVID-19) detection","author":"ghoshal","year":"2020","journal-title":"arXiv 2003 10769"},{"key":"ref91","article-title":"Covid-xpert: An ai powered population screening of covid-19 cases using chest radiography images","author":"li","year":"2020","journal-title":"arXiv 2004 03042"},{"key":"ref90","article-title":"Vetting security and privacy of global covid-19 contact tracing applications","author":"sun","year":"2020","journal-title":"arXiv 2006 10933"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1016\/j.hlpt.2018.03.002"},{"key":"ref99","article-title":"Uk phone masts attacked amid 5g-coronavirus conspiracy theory","author":"parveen","year":"0"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30461-X"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1080\/10410236.2017.1331312"},{"key":"ref82","article-title":"Report 9: Impact of non-pharmaceutical interventions (npis) to reduce covid19 mortality and healthcare demand","author":"ferguson","year":"2020"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1145\/3194658.3194665"},{"key":"ref84","article-title":"Simulation-based estimation of the spread of covid-19 in Iran","author":"ghaffarzadegan","year":"2020","journal-title":"medRxiv"},{"key":"ref83","doi-asserted-by":"crossref","first-page":"aaa4339","DOI":"10.1126\/science.aaa4339","article-title":"Modeling infectious disease dynamics in the complex landscape of global health","volume":"347","author":"heesterbeek","year":"2015","journal-title":"Science"},{"key":"ref80","author":"koerth","year":"2020","journal-title":"Why It's So Freaking Hard To Make A Good COVID-19 Model"},{"key":"ref89","year":"0","journal-title":"AI Could Help With the Next Pandemicbut not With This one"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1016\/S2214-109X(20)30074-7"},{"key":"ref86","doi-asserted-by":"crossref","DOI":"10.1126\/science.abb6936","article-title":"Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing","author":"ferretti","year":"2020","journal-title":"Sci"},{"key":"ref87","first-page":"1","article-title":"Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey in the populations when cities\/towns are under quarantine","author":"rao","year":"2020","journal-title":"Infection Contr Hosp Epidemiol"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2012.06.003"},{"key":"ref200","article-title":"Informational flow on Twitter–Corona virus outbreak–topic modelling approach","volume":"11","author":"kaila","year":"2020","journal-title":"Int J Adv Res Eng Technol"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1177\/0956797620939054"},{"key":"ref100","article-title":"Misinformation related to the 2019 20 coronavirus pandemic","year":"0"},{"key":"ref209","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(20)30132-8"},{"key":"ref203","doi-asserted-by":"publisher","DOI":"10.1039\/C8SC00148K"},{"key":"ref204","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/978-3-030-28954-6_18","article-title":"Interpretable deep learning in drug discovery","author":"preuer","year":"2019","journal-title":"Explainable AI Interpreting Explaining Visualizing Deep Learning"},{"key":"ref201","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3607228"},{"key":"ref202","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3561442"},{"key":"ref207","doi-asserted-by":"publisher","DOI":"10.1186\/s12967-020-02430-9"},{"key":"ref208","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30304-4"},{"key":"ref205","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.5b00559"},{"key":"ref206","doi-asserted-by":"publisher","DOI":"10.1016\/j.csbj.2020.03.025"},{"key":"ref211","article-title":"Global coalition to accelerate COVID-19 clinical research in resource-limited settings","year":"2020","journal-title":"The Lancet"},{"key":"ref210","article-title":"Target-specific and selective drug design for covid-19 using deep generative models","author":"chenthamarakshan","year":"2020","journal-title":"arXiv 2004 01215"},{"key":"ref212","article-title":"Multi-agent system for recruiting patients for clinical trials","author":"mahmoud","year":"2014"},{"key":"ref213","doi-asserted-by":"publisher","DOI":"10.1136\/bmjinnov-2015-000098"},{"key":"ref214","article-title":"Scopus, accessed on: 12-April-2020","year":"0"},{"key":"ref215","article-title":"CDC research Repositories, accessed on: 12-April-2020","year":"0"},{"key":"ref216","first-page":"993","article-title":"Latent dirichlet allocation","volume":"3","author":"blei","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref217","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.m1328"},{"key":"ref218","first-page":"10","article-title":"The use of Bayes and causal modelling in decision making, uncertainty and risk","volume":"12","author":"fenton","year":"2011","journal-title":"Council Eur Professional Inform Societies Upgrade"},{"key":"ref219","article-title":"Explainable artificial intelligence (XAI)","volume":"2","author":"gunning","year":"2017","journal-title":"Defense Adv Res Projects Agency nd Web"},{"key":"ref220","doi-asserted-by":"publisher","DOI":"10.1109\/MTS.2019.2930273"},{"key":"ref222","article-title":"The world after coronavirus, financial times","author":"harari","year":"0"},{"key":"ref221","article-title":"Secure and robust machine learning for healthcare: A survey","author":"qayyum","year":"2020","journal-title":"IEEE Rev Biomed Eng"},{"key":"ref229","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1038\/s42256-020-0172-7","article-title":"Pandemic data challenges","volume":"2","year":"2020","journal-title":"Nature Mach Intell"},{"key":"ref228","year":"2020","journal-title":"Call for Action Toward Building the Data Infrastructure and Ecosystem We Need to Tackle Pandemics and Other Dynamic Society and Environmental Threats"},{"key":"ref227","year":"2020","journal-title":"Statement Regarding the Ethical Implementation of Artificial Intelligence Systems (AIS) for Addressing the COVID-19 Pandemic"},{"key":"ref226","article-title":"Ethical Implications of the Use of AI to Manage the COVID-19 Outbreak","year":"2020"},{"key":"ref225","doi-asserted-by":"publisher","DOI":"10.1007\/s11023-018-9482-5"},{"key":"ref224","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2976612"},{"key":"ref223","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2018.2854776"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.20.22954"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020200642"},{"key":"ref125","article-title":"Review of artificial intelligence techniques in imaging data acquisition, segmentation and diagnosis for covid-19","author":"shi","year":"2020","journal-title":"EEE Rev Biomed Eng"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0204155"},{"key":"ref129","first-page":"1","article-title":"Deep learning system to screen Coronavirus disease 2019 pneumonia","author":"xu","year":"2020","journal-title":"Appl Intell"},{"key":"ref128","article-title":"A deep learning algorithm using CT images to screen for corona virus disease (COVID-19)","author":"wang","year":"2020","journal-title":"medRxiv"},{"key":"ref130","article-title":"Deep learning-based model for detecting 2019 novel Coronavirus pneumonia on high-resolution computed tomography: a prospective study","author":"chen","year":"2020","journal-title":"medRxiv"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020200905"},{"key":"ref134","article-title":"The ionising radiation (medical exposure) regulations 2017","year":"2017"},{"key":"ref131","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-030-00889-5_1","article-title":"Unet++: A nested u-net architecture for medical image segmentation","author":"zhou","year":"2018","journal-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support"},{"key":"ref132","article-title":"Rapid AI development cycle for the Coronavirus (COVID-19) pandemic: Initial results for automated detection & patient monitoring using deep learning CT image analysis","author":"gozes","year":"2020","journal-title":"arXiv 2003 05037"},{"key":"ref232","doi-asserted-by":"publisher","DOI":"10.1007\/s11023-020-09517-8"},{"key":"ref233","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139046855.020"},{"key":"ref230","article-title":"Contact tracing in the real world","author":"anderson","year":"2020"},{"key":"ref231","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0088-2"},{"key":"ref239","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020201187"},{"key":"ref238","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020200847"},{"key":"ref235","first-page":"1310","article-title":"Privacy-preserving deep learning","author":"shokri","year":"0","journal-title":"Proc 22nd ACM SIGSAC Conf Comput Commun Secur"},{"key":"ref234","first-page":"423","article-title":"Privacy, algorithms, and artificial intelligence","author":"tucker","year":"2018","journal-title":"In the Economics of Artificial Intelligence An Agenda"},{"key":"ref237","doi-asserted-by":"publisher","DOI":"10.1007\/s00134-020-05996-6"},{"key":"ref236","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0929-x"},{"key":"ref136","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref135","article-title":"COVIDX-Net: A framework of deep learning classifiers to diagnose COVID-19 in X-Ray images","author":"hemdan","year":"2020","journal-title":"arXiv 2003 11055"},{"key":"ref138","article-title":"Automatic detection of Coronavirus disease (COVID-19) using x-ray images and deep convolutional neural networks","author":"narin","year":"2020","journal-title":"arXiv 2003 10849"},{"key":"ref137","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"arXiv 1704 04861"},{"key":"ref139","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref140","article-title":"COVID-ResNet: A deep learning framework for screening of COVID19 from radiographs","author":"farooq","year":"2020","journal-title":"arXiv 2003 14395"},{"key":"ref141","article-title":"Detection of coronavirus disease (covid-19) based on deep features","author":"sethy","year":"2020","journal-title":"Preprints"},{"key":"ref142","article-title":"Lunit CXR for COVID-19; Chest X-ray solutions","year":"2020"},{"key":"ref143","article-title":"VUNO Med-LungQuant & Chest X-ray solutions","year":"2020"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30260-9"},{"key":"ref144","article-title":"English dictionaries, gold and silver standard corpora for biomedical natural language processing related to SARS-CoV-2 and COVID-19","author":"rashed","year":"2020","journal-title":"arXiv 2003 09865"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30183-5"},{"key":"ref145","article-title":"Understanding the perception of COVID-19 policies by mining a multilanguage Twitter dataset","author":"lopez","year":"2020","journal-title":"arXiv 2003 10359"},{"key":"ref241","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2783118"},{"key":"ref242","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2710800"},{"key":"ref243","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v35i3.2529"},{"key":"ref240","doi-asserted-by":"publisher","DOI":"10.1016\/S2468-2667(20)30085-2"},{"key":"ref109","year":"0","journal-title":"Diabetes Manegmet and COVID-19"},{"key":"ref108","article-title":"CLEW Medical, accessed on: 1-April-2020","year":"0"},{"key":"ref107","year":"0","journal-title":"New FDA Guidance Allows Use of KardiaMobile 6L to Measure QTc in COVID-19 Patients"},{"key":"ref106","article-title":"AliveCor","year":"0"},{"key":"ref105","article-title":"Health Care Workers' Stress Compounded By Long Days And Concerns About People Not Taking COVID-19 Seriously","year":"0"},{"key":"ref104","article-title":"WHO and Rakuten Viber Fight COVID-19 Misinformation With Inter- 1318 active Chatbot","year":"0"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.3386\/w26867"},{"key":"ref102","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.3547729","article-title":"The global macroeconomic impacts of COVID-19: Seven scenarios","author":"mckibbin","year":"2020"},{"key":"ref111","year":"0","journal-title":"Secretary Azar Announces Historic Expansion of Telehealth Access to Combat COVID-19"},{"key":"ref112","year":"0","journal-title":"COVID-19 Telehealth Program"},{"key":"ref110","year":"0","journal-title":"COVID-19 Home Pulse Oximetry Could Be Game Changer Says ER Doc"},{"key":"ref10","article-title":"Artificial intelligence in radiology","year":"2020"},{"key":"ref11","article-title":"COVID-19 community mobility reports","year":"2020"},{"key":"ref12","article-title":"COVID-19 DATABASE","year":"0"},{"key":"ref13","article-title":"CORD-19 research challenge","year":"2020"},{"key":"ref14","article-title":"European Centre for Disease Prevention and Control (ECDC)","year":"2020"},{"key":"ref15","article-title":"Coronavirus (covid19) tweets","year":"2020"},{"key":"ref16","article-title":"COVID-19 Korea Dataset with Patient Routes","year":"2020"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1038\/nrd1927"},{"key":"ref17","article-title":"COVID-19 Hospital Impact Model for Epidemics","year":"2020"},{"key":"ref117","first-page":"138","article-title":"An agent-based approach to real-time patient identification for clinical trials","author":"tyson","year":"2011","journal-title":"Proc Int Conf Electron Healthcare"},{"key":"ref18","article-title":"Global research on novel coronavirus-2019","year":"2020"},{"key":"ref19","article-title":"Genomic epidemiology of hCoV-19","year":"2020"},{"key":"ref119","article-title":"Network medicine framework for identifying drug repurposing opportunities for covid-19","author":"gysi","year":"2020","journal-title":"arXiv 2004 07229"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.4155\/fmc-2018-0158"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30818-7"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1021\/acs.molpharmaceut.8b00930"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2018.11.014"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1016\/j.trsl.2017.10.010"},{"key":"ref121","first-page":"1","article-title":"Retrospective motion correction in multishot MRI using generative adversarial network","volume":"10","author":"usman","year":"2020","journal-title":"Scientific Rept"},{"key":"ref122","first-page":"1","article-title":"Volumetric lung nodule segmentation using adaptive roi with multi-view residual learning","volume":"10","author":"usman","year":"2020"},{"key":"ref123","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-51503-3","article-title":"Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems","volume":"9","author":"qin","year":"2019","journal-title":"Scientific Reports"}],"container-title":["IEEE Transactions on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/9078688\/9271839\/9184922-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9078688\/9271839\/09184922.pdf?arnumber=9184922","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T01:09:54Z","timestamp":1755911394000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9184922\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":243,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tai.2020.3020521","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.12212516.v1","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.12212516.v2","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.12212516","asserted-by":"object"}]},"ISSN":["2691-4581"],"issn-type":[{"value":"2691-4581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8]]}}}