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010   $a3-319-77911-7
024 7 $a10.1007/978-3-319-77911-9
035   $a(CKB)4100000003359562
035   $a(MiAaPQ)EBC5356271
035   $a(DE-He213)978-3-319-77911-9
035   $a(PPN)226696146
035   $a(EXLCZ)994100000003359562
100   $a20180420d2018      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aAdvanced Data Analytics in Health /$fedited by Philippe J. Giabbanelli, Vijay K. Mago, Elpiniki I. Papageorgiou
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (221 pages)
225 1 $aSmart Innovation, Systems and Technologies,$x2190-3018 ;$v93
311   $a3-319-77910-9 
327   $aDimensionality Reduction for Exploratory Data Analysis in Daily Medical Research -- Navigating Complex Systems for Policymaking using Simple Software Tools -- An Agent-based Model of Healthy Eating with Applications to Hypertension -- Young Adults, Health Insurance Expansions and Hospital Services Utilization -- The Impact of Patient Incentives on Comprehensive Diabetes Care Services and Medical Expenditures -- Challenges and Cases of Genomic Data Integration Across Technologies and Biological Scales.
330   $aThis book introduces readers to the methods, types of data, and scale of analysis used in the context of health. The challenges of working with big data are explored throughout the book, while the benefits are also emphasized through the discoveries made possible by linking large datasets. Methods include thorough case studies from statistics, as well as the newest facets of data analytics: data visualization, modeling and simulation, and machine learning. The diversity of datasets is illustrated through chapters on networked data, image processing, and text, in addition to typical structured numerical datasets. While the methods, types of data, and scale have been individually covered elsewhere, by bringing them all together under one ?umbrella? the book highlights synergies, while also helping scholars fluidly switch between tools as needed. New challenges and emerging frontiers are also discussed, helping scholars grasp how methods will need to change in response to the latest challenges in health.
410  0$aSmart Innovation, Systems and Technologies,$x2190-3018 ;$v93
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aHealth informatics
606   $aBig data
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009
606   $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070
606   $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aHealth informatics.
615  0$aBig data.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aHealth Informatics.
615 24$aBig Data/Analytics.
615 24$aHealth Informatics.
676   $a610.285
702   $aGiabbanelli$b Philippe J$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aMago$b Vijay K$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aPapageorgiou$b Elpiniki I$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910299940903321
996   $aAdvanced Data Analytics in Health$92530027
997   $aUNINA