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001447009 001__ 1447009
001447009 003__ OCoLC
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001447009 020__ $$a9783030952815$$q(electronic bk.)
001447009 020__ $$a3030952819$$q(electronic bk.)
001447009 020__ $$z9783030952808
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001447009 0247_ $$a10.1007/978-3-030-95281-5$$2doi
001447009 035__ $$aSP(OCoLC)1320812203
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001447009 049__ $$aISEA
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001447009 08204 $$a614.402/85$$223/eng/20220526
001447009 24500 $$aEpidemic analytics for decision supports in COVID19 crisis /$$cJoao Alexandre Lobo Marques, Simon James Fong, editors.
001447009 264_1 $$aCham :$$bSpringer,$$c[2022]
001447009 264_4 $$c©2022
001447009 300__ $$a1 online resource (vi, 158 pages) :$$billustrations (chiefly color)
001447009 336__ $$atext$$btxt$$2rdacontent
001447009 337__ $$acomputer$$bc$$2rdamedia
001447009 338__ $$aonline resource$$bcr$$2rdacarrier
001447009 5050_ $$aChapter 1. Research and Technology Development Achievements During the COVID-19 Pandemic - An Overview -- Chapter 2. Analysis of the COVID-19 Pandemic Behavior based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models -- Chapter 3. The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak -- Chapter 4. Probabilistic Forecasting Model for the COVID-19 Pandemic based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System -- Chapter 5. The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID-19 Pandemic -- Chapter 6. A Quantum Field formulation for a pandemic propagation.
001447009 506__ $$aAccess limited to authorized users.
001447009 520__ $$aCovid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.
001447009 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed May 26, 2022).
001447009 650_0 $$aEpidemiology$$xData processing.
001447009 650_0 $$aEpidemiology$$xDecision making.
001447009 650_0 $$aCOVID-19 (Disease)$$xData processing.
001447009 650_0 $$aDecision making$$xData processing.
001447009 655_0 $$aElectronic books.
001447009 7001_ $$aMarques, Joao Alexandre Lobo,$$eeditor.
001447009 7001_ $$aFong, Simon,$$eeditor.
001447009 77608 $$iPrint version:$$z3030952800$$z9783030952808$$w(OCoLC)1289478812
001447009 852__ $$bebk
001447009 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-95281-5$$zOnline Access$$91397441.1
001447009 909CO $$ooai:library.usi.edu:1447009$$pGLOBAL_SET
001447009 980__ $$aBIB
001447009 980__ $$aEBOOK
001447009 982__ $$aEbook
001447009 983__ $$aOnline
001447009 994__ $$a92$$bISE