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020			_a9783030952815
024	7		_a10.1007/978-3-030-95281-5 _2doi
040			_aTR-AnTOB _beng _erda _cTR-AnTOB
041			_aeng
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245	1	0	_aEpidemic Analytics for Decision Supports in COVID19 Crisis _h[electronic resource] / _cedited by Joao Alexandre Lobo Marques, Simon James Fong.
250			_a1st ed. 2022.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_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.
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.
650		0	_aIndustrial Management.
650		0	_aEpidemiology.
650		0	_aOperations research.
650		0	_aData mining.
650		0	_aMedicine, Preventive.
650		0	_aHealth promotion.
650	1	4	_aIndustrial Management.
650	2	4	_aEpidemiology.
650	2	4	_aOperations Research and Decision Theory.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aHealth Promotion and Disease Prevention.
653		0	_aCOVID-19 -- epidemiology
653		0	_aDecision Support Systems, Clinical
653		0	_aDecision Support Techniques
653		0	_aElectronic Data Processing
653		0	_aEpidemiologic Methods
700	1		_aMarques, Joao Alexandre Lobo. _eeditor. _0(orcid)0000-0002-6472-8784 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aFong, Simon James. _eeditor. _0(orcid)0000-0002-1848-7246 _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
856	4	0	_uhttps://doi.org/10.1007/978-3-030-95281-5 _3Springer eBooks _zOnline access link to the resource
942			_2NLM _cEBK