{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:45:38Z","timestamp":1767339938355,"version":"3.40.3"},"reference-count":65,"publisher":"Springer Science and Business Media LLC","issue":"17","license":[{"start":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T00:00:00Z","timestamp":1652486400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T00:00:00Z","timestamp":1652486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61273300"],"award-info":[{"award-number":["61273300"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001381","name":"National Research Foundation Singapore","doi-asserted-by":"publisher","award":["AISG2-RP-2020-019"],"award-info":[{"award-number":["AISG2-RP-2020-019"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Singapore Ministry of Education Academic Research Fund","award":["19-C220-SMU-023"],"award-info":[{"award-number":["19-C220-SMU-023"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62103428","62103420"],"award-info":[{"award-number":["62103428","62103420"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102432","62103425"],"award-info":[{"award-number":["62102432","62103425"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2021JJ40702","2021JJ40697"],"award-info":[{"award-number":["2021JJ40702","2021JJ40697"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1007\/s00521-022-07210-8","type":"journal-article","created":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T18:03:11Z","timestamp":1652551391000},"page":"14859-14879","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Who are the \u2018silent spreaders\u2019?: contact tracing in spatio-temporal memory models"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8115-7020","authenticated-orcid":false,"given":"Yue","family":"Hu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Budhitama","family":"Subagdja","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ah-Hwee","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chai","family":"Quek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quanjun","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,14]]},"reference":[{"key":"7210_CR1","unstructured":"Wang Y, Tong J, Qin Y, Xie T, Li J, Li J, Xiang J, Cui Y, Higgs ES, Xiang J et al (2020) Characterization of an asymptomatic cohort of SARS-CoV-2 infected individuals outside of Wuhan, China. Clinical Infectious Diseases, 1\u20137"},{"issue":"5","key":"7210_CR2","doi-asserted-by":"publisher","first-page":"672","DOI":"10.1038\/s41591-020-0869-5","volume":"26","author":"X He","year":"2020","unstructured":"He X, Lau EH, Wu P, Deng X, Wang J, Hao X, Lau YC, Wong JY, Guan Y, Tan X et al (2020) Temporal dynamics in viral shedding and transmissibility of COVID-19. Nature Med 26(5):672\u2013675","journal-title":"Nature Med"},{"issue":"7","key":"7210_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3201\/eid2607.201595","volume":"26","author":"NW Furukawa","year":"2020","unstructured":"Furukawa NW, Brooks JT, Sobel J (2020) Evidence supporting transmission of severe acute respiratory syndrome coronavirus 2 while presymptomatic or asymptomatic. Emerg Infect Dis 26(7):1\u20136","journal-title":"Emerg Infect Dis"},{"issue":"8","key":"7210_CR4","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1038\/s41591-020-0965-6","volume":"26","author":"Q-X Long","year":"2020","unstructured":"Long Q-X, Tang X-J, Shi Q-L, Li Q, Deng H-J, Yuan J, Hu J-L, Xu W, Zhang Y, Lv F-J et al (2020) Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nature Med 26(8):1200\u20131204","journal-title":"Nature Med"},{"key":"7210_CR5","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.ins.2021.01.084","volume":"561","author":"C Zhan","year":"2021","unstructured":"Zhan C, Chen J, Zhang H (2021) An investigation of testing capacity for evaluating and modeling the spread of coronavirus disease. Inf Sci 561:211\u2013229","journal-title":"Inf Sci"},{"key":"7210_CR6","doi-asserted-by":"crossref","unstructured":"Lee S, Kim T, Lee E, Lee C, Kim H, Rhee H, Park SY, Son H-J, Yu S, Park JW et al (2020) Clinical course and molecular viral shedding among asymptomatic and symptomatic patients with SARS-CoV-2 infection in a community treatment center in the Republic of Korea. JAMA Internal Medicine, 1\u20136","DOI":"10.1001\/jamainternmed.2020.3862"},{"issue":"5","key":"7210_CR7","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1007\/s11427-020-1661-4","volume":"63","author":"Z Hu","year":"2020","unstructured":"Hu Z, Song C, Xu C, Jin G, Chen Y, Xu X, Ma H, Chen W, Lin Y, Zheng Y et al (2020) Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China. Sci China Life Sci 63(5):706\u2013711","journal-title":"Sci China Life Sci"},{"issue":"14","key":"7210_CR8","doi-asserted-by":"publisher","first-page":"1406","DOI":"10.1001\/jama.2020.2565","volume":"323","author":"Y Bai","year":"2020","unstructured":"Bai Y, Yao L, Wei T, Tian F, Jin D-Y, Chen L, Wang M (2020) Presumed asymptomatic carrier transmission of COVID-19. JAMA 323(14):1406\u20131407","journal-title":"JAMA"},{"issue":"6","key":"7210_CR9","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/S1473-3099(20)30198-5","volume":"20","author":"H Qiu","year":"2020","unstructured":"Qiu H, Wu J, Hong L, Luo Y, Song Q, Chen D (2020) Clinical and epidemiological features of 36 children with coronavirus disease 2019 (COVID-19) in Zhejiang, China: an observational cohort study. Lancet Infect Dis 20(6):689\u2013696","journal-title":"Lancet Infect Dis"},{"issue":"10","key":"7210_CR10","doi-asserted-by":"publisher","first-page":"2000180","DOI":"10.2807\/1560-7917.ES.2020.25.10.2000180","volume":"25","author":"K Mizumoto","year":"2020","unstructured":"Mizumoto K, Kagaya K, Zarebski A, Chowell G (2020) Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveillance 25(10):2000180","journal-title":"Eurosurveillance"},{"issue":"4","key":"7210_CR11","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1016\/j.jinf.2020.02.018","volume":"80","author":"S Tian","year":"2020","unstructured":"Tian S, Hu N, Lou J, Chen K, Kang X, Xiang Z, Chen H, Wang D, Liu N, Liu D et al (2020) Characteristics of COVID-19 infection in Beijing. J Infect 80(4):401\u2013406","journal-title":"J Infect"},{"key":"7210_CR12","unstructured":"Cho H, Ippolito D, Yu, YW (2020) Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs. arXiv:2003.11511"},{"key":"7210_CR13","unstructured":"Kim MJ, Denyer S (2020) A travel log of the times in South Korea: Mapping the movements of coronavirus carriers. https:\/\/www.washingtonpost.com\/world\/asia_pacific\/coronavirus-south-korea-tracking-apps\/2020\/03\/13\/2bed568e-5fac-11ea-ac50-18701e14e06d_story.html"},{"key":"7210_CR14","unstructured":"Koh D (2020) Australia\u2019s COVIDSafe contact tracing app sees 2 million downloads within 1 day of launch. https:\/\/www.mobihealthnews.com\/news\/asia-pacific\/australia-s-covidsafe-contact-tracing-app-sees-2-million-downloads-within-1-day"},{"key":"7210_CR15","unstructured":"MacKay J (2020) Tracking your location and targeted texts: how sharing your data could help in New Zealand\u2019s level 4 lockdown. https:\/\/theconversation.com\/tracking-your-location-and-targeted-texts-how-sharing-your-data-could-help-in-new-zealands-level-4-lockdown-134894"},{"issue":"14","key":"7210_CR16","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1001\/jama.2020.3151","volume":"323","author":"CJ Wang","year":"2020","unstructured":"Wang CJ, Ng CY, Brook RH (2020) Response to COVID-19 in Taiwan: Big data analytics, new technology, and proactive testing. JAMA 323(14):1341\u20131342","journal-title":"JAMA"},{"key":"7210_CR17","unstructured":"Abbas R, Michael K (2020) The coronavirus contact tracing app won\u2019t log your location, but it will reveal who you hang out with. https:\/\/theconversation.com\/the-coronavirus-contact-tracing-app-wont-log-your-location-but-it-will-reveal-who-you-hang-out-with-136387"},{"key":"7210_CR18","doi-asserted-by":"crossref","unstructured":"Tan L, Yu K, Bashir AK, Cheng X, Ming F, Zhao L, Zhou X (2021) Toward real-time and efficient cardiovascular monitoring for COVID-19 patients by 5G-enabled wearable medical devices: a deep learning approach. Neural Comput Appl, 1\u201314","DOI":"10.1007\/s00521-021-06219-9"},{"issue":"1","key":"7210_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-020-79000-y","volume":"10","author":"J Almagor","year":"2020","unstructured":"Almagor J, Picascia S (2020) Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model. Sci Rep 10(1):1\u201311","journal-title":"Sci Rep"},{"issue":"10","key":"7210_CR20","doi-asserted-by":"publisher","first-page":"6989","DOI":"10.1126\/sciadv.abd6989","volume":"7","author":"NE Kogan","year":"2021","unstructured":"Kogan NE, Clemente L, Liautaud P, Kaashoek J, Link NB, Nguyen AT, Lu FS, Huybers P, Resch B, Havas C et al (2021) An early warning approach to monitor Covid-19 activity with multiple digital traces in near real time. Sci Adv 7(10):6989","journal-title":"Sci Adv"},{"key":"7210_CR21","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.ins.2021.04.021","volume":"570","author":"L Ouyang","year":"2021","unstructured":"Ouyang L, Yuan Y, Cao Y, Wang F-Y (2021) A novel framework of collaborative early warning for Covid-19 based on blockchain and smart contracts. Inf Sci 570:124\u2013143","journal-title":"Inf Sci"},{"issue":"10","key":"7210_CR22","doi-asserted-by":"publisher","first-page":"1574","DOI":"10.1109\/TNNLS.2012.2208477","volume":"23","author":"W Wang","year":"2012","unstructured":"Wang W, Subagdja B, Tan A-H, Starzyk JA (2012) Neural modeling of episodic memory: encoding, retrieval, and forgetting. IEEE Trans Neural Netw Learn Syst 23(10):1574\u20131586","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"7210_CR23","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/j.neucom.2015.02.038","volume":"161","author":"B Subagdja","year":"2015","unstructured":"Subagdja B, Tan A-H (2015) Neural modeling of sequential inferences and learning over episodic memory. Neurocomputing 161:229\u2013242","journal-title":"Neurocomputing"},{"key":"7210_CR24","doi-asserted-by":"crossref","unstructured":"Chang P-H, Tan A-H (2017) Encoding and recall of spatio-temporal episodic memory in real time. In: International Joint Conference on Artificial Intelligence, pp. 1490\u20131496","DOI":"10.24963\/ijcai.2017\/206"},{"key":"7210_CR25","unstructured":"Hu Y, Subagdja, B, Tan, A-H, Quek C, Yin Q (2020) Who are the \u2018silent spreaders\u2019?: Contact tracing in spatio-temporal memory models. arXiv:2010.00187"},{"issue":"10223","key":"7210_CR26","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1016\/S0140-6736(20)30154-9","volume":"395","author":"JF-W Chan","year":"2020","unstructured":"Chan JF-W, Yuan S, Kok K-H, To KK-W, Chu H, Yang J, Xing F, Liu J, Yip CC-Y, Poon RW-S et al (2020) A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. The Lancet 395(10223):514\u2013523","journal-title":"The Lancet"},{"key":"7210_CR27","unstructured":"Min CH (2020) Almost a quarter of infected household members of COVID-19 patients were asymptomatic, Singapore study finds. https:\/\/www.channelnewsasia.com\/news\/singapore\/infected-household-members-covid-19-asymptomatic-12803192. 04 June"},{"key":"7210_CR28","doi-asserted-by":"crossref","unstructured":"Day M (2020) Covid-19: identifying and isolating asymptomatic people helped eliminate virus in Italian village. BMJ: British Medical Journal (Online) 368","DOI":"10.1136\/bmj.m1165"},{"key":"7210_CR29","unstructured":"Carl\u00a0Heneghan, Jon\u00a0Brassey TJ (2020) COVID-19: What proportion are asymptomatic? https:\/\/www.cebm.net\/covid-19\/covid-19-what-proportion-are-asymptomatic\/. 6 April"},{"key":"7210_CR30","doi-asserted-by":"crossref","unstructured":"Oran DP, Topol EJ (2020) Prevalence of asymptomatic SARS-CoV-2 infection: A narrative review. Annals of Internal Medicine, 1\u20137","DOI":"10.7326\/M20-3012"},{"key":"7210_CR31","unstructured":"World Health Organization (2020) Q&A: Influenza and COVID-19 - similarities and differences. https:\/\/www.who.int\/emergencies\/diseases\/novel-coronavirus-2019\/question-and-answers-hub\/q-a-detail\/q-a-similarities-and-differences-covid-19-and-influenza. 17 March"},{"key":"7210_CR32","doi-asserted-by":"crossref","unstructured":"Day M (2020) Covid-19: four fifths of cases are asymptomatic, China figures indicate. British Medical Journal Publishing Group","DOI":"10.1136\/bmj.m1375"},{"key":"7210_CR33","first-page":"027","volume":"54","author":"W Sun","year":"2020","unstructured":"Sun W, Ling F, Pan J, Cai J, Miao Z, Liu S, Cheng W, Chen E (2020) Epidemiological characteristics of 2019 novel coronavirus family clustering in Zhejiang Province. Chin J Prevent Med 54:027\u2013027","journal-title":"Chin J Prevent Med"},{"key":"7210_CR34","doi-asserted-by":"crossref","unstructured":"Lavezzo E, Franchin E, Ciavarella C, Cuomo-Dannenburg G, Barzon L, Del\u00a0Vecchio C, Rossi L, Manganelli R, Loregian A, Navarin N et al (2020) Suppression of COVID-19 outbreak in the municipality of Vo, Italy. medRxiv","DOI":"10.1101\/2020.04.17.20053157"},{"key":"7210_CR35","doi-asserted-by":"crossref","unstructured":"Loey M, Manogaran G, Khalifa NEM (2020) A deep transfer learning model with classical data augmentation and CGAN to detect COVID-19 from chest CT radiography digital images. Neural Comput Appl 1\u201313","DOI":"10.1007\/s00521-020-05437-x"},{"key":"7210_CR36","doi-asserted-by":"crossref","unstructured":"Madhavan MV, Khamparia A, Gupta D, Pande S, Tiwari P, Hossain MS (2021) Res-covnet: an internet of medical health things driven Covid-19 framework using transfer learning. Neural Comput Appl 1\u201314","DOI":"10.1007\/s00521-021-06171-8"},{"key":"7210_CR37","doi-asserted-by":"publisher","first-page":"2158","DOI":"10.1056\/NEJMe2009758","volume":"382","author":"M Gandhi","year":"2020","unstructured":"Gandhi M, Yokoe DS, Havlir DV (2020) Asymptomatic transmission, the Achilles\u2019 heel of current strategies to control COVID-19. New Engl J Med 382:2158\u20132160","journal-title":"New Engl J Med"},{"key":"7210_CR38","doi-asserted-by":"crossref","unstructured":"Rahimi I, Chen F, Gandomi AH (2021) A review on Covid-19 forecasting models. Neural Comput Appl 1\u201311","DOI":"10.21203\/rs.3.rs-83965\/v1"},{"issue":"772","key":"7210_CR39","first-page":"700","volume":"115","author":"WO Kermack","year":"1927","unstructured":"Kermack WO, McKendrick AG (1927) A contribution to the mathematical theory of epidemics. Proc R Soc lond Ser A Contain Papers Math Phys Character 115(772):700\u2013721","journal-title":"Proc R Soc lond Ser A Contain Papers Math Phys Character"},{"key":"7210_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113970","volume":"165","author":"IN Lymperopoulos","year":"2021","unstructured":"Lymperopoulos IN (2021) # stayhome to contain covid-19: neuro-sir-neurodynamical epidemic modeling of infection patterns in social networks. Expert Syst Appl 165:113970","journal-title":"Expert Syst Appl"},{"issue":"3\u20134","key":"7210_CR41","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1016\/j.ecolmodel.2007.01.020","volume":"204","author":"Z Zhang","year":"2007","unstructured":"Zhang Z (2007) The outbreak pattern of SARS cases in China as revealed by a mathematical model. Ecol modell 204(3\u20134):420\u2013426","journal-title":"Ecol modell"},{"issue":"2","key":"7210_CR42","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.bsheal.2020.03.004","volume":"2","author":"M D\u2019Arienzo","year":"2020","unstructured":"D\u2019Arienzo M, Coniglio A (2020) Assessment of the SARS-CoV-2 basic reproduction number, R0, based on the early phase of COVID-19 outbreak in Italy. Biosaf Health 2(2):57\u201359","journal-title":"Biosaf Health"},{"key":"7210_CR43","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.epidem.2017.02.010","volume":"22","author":"S Venkatramanan","year":"2018","unstructured":"Venkatramanan S, Lewis B, Chen J, Higdon D, Vullikanti A, Marathe M (2018) Using data-driven agent-based models for forecasting emerging infectious diseases. Epidemics 22:43\u201349","journal-title":"Epidemics"},{"issue":"9","key":"7210_CR44","doi-asserted-by":"publisher","first-page":"1417","DOI":"10.1038\/s41591-020-1001-6","volume":"26","author":"N Hoertel","year":"2020","unstructured":"Hoertel N, Blachier M, Blanco C, Olfson M, Massetti M, Rico MS, Limosin F, Leleu H (2020) A stochastic agent-based model of the SARS-CoV-2 epidemic in France. Nature Med 26(9):1417\u20131421","journal-title":"Nature Med"},{"issue":"9","key":"7210_CR45","doi-asserted-by":"publisher","first-page":"964","DOI":"10.1038\/s41562-020-0931-9","volume":"4","author":"A Aleta","year":"2020","unstructured":"Aleta A, Martin-Corral D, y Piontti AP, Ajelli M, Litvinova M, Chinazzi M, Dean NE, Halloran ME, Longini IM Jr, Merler S et al (2020) Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nature Hum Behaviour 4(9):964\u2013971","journal-title":"Nature Hum Behaviour"},{"issue":"1","key":"7210_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-020-20325-7","volume":"12","author":"WJ Bradshaw","year":"2021","unstructured":"Bradshaw WJ, Alley EC, Huggins JH, Lloyd AL, Esvelt KM (2021) Bidirectional contact tracing could dramatically improve COVID-19 control. Nature Commun 12(1):1\u20139","journal-title":"Nature Commun"},{"key":"7210_CR47","doi-asserted-by":"crossref","unstructured":"Kojaku S, H\u00e9bert-Dufresne, L, Mones E, Lehmann S, Ahn Y-Y (2021) The effectiveness of backward contact tracing in networks. Nature Physics, 1\u20137","DOI":"10.1038\/s41567-021-01187-2"},{"key":"7210_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113661","volume":"160","author":"MM Ahamad","year":"2020","unstructured":"Ahamad MM, Aktar S, Rashed-Al-Mahfuz M, Uddin S, Li\u00f2 P, Xu H, Summers MA, Quinn JM, Moni MA (2020) A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients. Expert Syst Appl 160:113661","journal-title":"Expert Syst Appl"},{"issue":"5","key":"7210_CR49","doi-asserted-by":"publisher","first-page":"1052","DOI":"10.3201\/eid2605.200198","volume":"26","author":"Z-D Tong","year":"2020","unstructured":"Tong Z-D, Tang A, Li K-F, Li P, Wang H-L, Yi J-P, Zhang Y-L, Yan J-B (2020) Potential presymptomatic transmission of SARS-CoV-2, Zhejiang province, China, 2020. Emerg Infect Dis 26(5):1052","journal-title":"Emerg Infect Dis"},{"issue":"13","key":"7210_CR50","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1056\/NEJMoa2001316","volume":"382","author":"Q Li","year":"2020","unstructured":"Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KS, Lau EH, Wong JY et al (2020) Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. New Engl J Med 382(13):1199\u20131207","journal-title":"New Engl J Med"},{"issue":"5","key":"7210_CR51","doi-asserted-by":"publisher","first-page":"2000062","DOI":"10.2807\/1560-7917.ES.2020.25.5.2000062","volume":"25","author":"JA Backer","year":"2020","unstructured":"Backer JA, Klinkenberg D, Wallinga J (2020) Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20\u201328 January 2020. Eurosurveillance 25(5):2000062","journal-title":"Eurosurveillance"},{"issue":"9","key":"7210_CR52","doi-asserted-by":"publisher","first-page":"577","DOI":"10.7326\/M20-0504","volume":"172","author":"SA Lauer","year":"2020","unstructured":"Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, Azman AS, Reich NG, Lessler J (2020) The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Ann Internal Med 172(9):577\u2013582","journal-title":"Ann Internal Med"},{"issue":"2","key":"7210_CR53","doi-asserted-by":"publisher","first-page":"538","DOI":"10.3390\/jcm9020538","volume":"9","author":"NM Linton","year":"2020","unstructured":"Linton NM, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov AR, Jung S-M, Yuan B, Kinoshita R, Nishiura H (2020) Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data. J Clin Med 9(2):538","journal-title":"J Clin Med"},{"issue":"1","key":"7210_CR54","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/S0734-189X(87)80014-2","volume":"37","author":"GA Carpenter","year":"1987","unstructured":"Carpenter GA, Grossberg S (1987) A massively parallel architecture for a self-organizing neural pattern recognition machine. Comput Vis Graph Image Process 37(1):54\u2013115","journal-title":"Comput Vis Graph Image Process"},{"key":"7210_CR55","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.neunet.2019.09.014","volume":"120","author":"L Meng","year":"2019","unstructured":"Meng L, Tan A-H, Miao C (2019) Salience-aware adaptive resonance theory for large-scale sparse data clustering. Neural Netw 120:143\u2013157","journal-title":"Neural Netw"},{"key":"7210_CR56","doi-asserted-by":"crossref","unstructured":"Tan A-H, Carpenter GA, Grossberg S (2007) Intelligence through interaction: Towards a unified theory for learning. In: International Symposium on Neural Networks, pp. 1094\u20131103. Springer","DOI":"10.1007\/978-3-540-72383-7_128"},{"issue":"5","key":"7210_CR57","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1109\/TNNLS.2014.2327636","volume":"26","author":"T-H Teng","year":"2014","unstructured":"Teng T-H, Tan A-H, Zurada JM (2014) Self-organizing neural networks integrating domain knowledge and reinforcement learning. IEEE Trans Neural Netw Learn Syst 26(5):889\u2013902","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"7210_CR58","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.neunet.2019.08.020","volume":"120","author":"A-H Tan","year":"2019","unstructured":"Tan A-H, Subagdja B, Wang D, Meng L (2019) Self-organizing neural networks for universal learning and multimodal memory encoding. Neural Netw 120:58\u201373","journal-title":"Neural Netw"},{"issue":"1","key":"7210_CR59","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1109\/TKDE.2019.2924623","volume":"33","author":"S Gao","year":"2019","unstructured":"Gao S, Tan A-H, Setchi R (2019) Learning adl daily routines with spatiotemporal neural networks. IEEE Trans Knowl Data Eng 33(1):143\u2013153","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"7210_CR60","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1016\/0893-6080(91)90056-B","volume":"4","author":"GA Carpenter","year":"1991","unstructured":"Carpenter GA, Grossberg S, Rosen DB (1991) Fuzzy art: fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Netw 4(6):759\u2013771","journal-title":"Neural Netw"},{"key":"7210_CR61","unstructured":"Woodward A (2020) Coronavirus super-spreader events all have notable similarities \u2013 and they reveal the types of gatherings we should avoid for years. https:\/\/www.businessinsider.com\/coronavirus-super-spreader-events-reveal-gatherings-to-avoid-2020-5"},{"issue":"10225","key":"7210_CR62","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/S0140-6736(20)30260-9","volume":"395","author":"JT Wu","year":"2020","unstructured":"Wu JT, Leung K, Leung GM (2020) Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet 395(10225):689\u2013697","journal-title":"The Lancet"},{"key":"7210_CR63","unstructured":"Volz E, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunub\u00e1 Z, Cuomo-Dannenburg G, Donnelly CA Dorigatti I, FitzJohn R, et al (2020) Report 5: phylogenetic analysis of SARS-CoV-2. Imperial College London COVID-19 Response Team"},{"key":"7210_CR64","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.neunet.2012.09.018","volume":"37","author":"T Kohonen","year":"2013","unstructured":"Kohonen T (2013) Essentials of the self-organizing map. Neural Netw 37:52\u201365","journal-title":"Neural Netw"},{"issue":"3","key":"7210_CR65","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1080\/14494035.2020.1783789","volume":"39","author":"J Woo","year":"2020","unstructured":"Woo J (2020) Policy capacity and Singapore\u2019s response to the COVID-19 pandemic. Policy Soc 39(3):345\u2013362","journal-title":"Policy Soc"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-07210-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-022-07210-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-07210-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T16:46:04Z","timestamp":1744130764000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-022-07210-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,14]]},"references-count":65,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["7210"],"URL":"https:\/\/doi.org\/10.1007\/s00521-022-07210-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2022,5,14]]},"assertion":[{"value":"26 October 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors declare that no conflict of interest exists.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}