國立虎尾科技大學 |

Advanced Data Analytics in Health

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advanced Data Analytics in Health/ edited by Philippe J. Giabbanelli, Vijay K. Mago, Elpiniki I. Papageorgiou.
other author:	Giabbanelli, Philippe J.
Description:	XIV, 216 p.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-77911-9
ISBN:	9783319779119

Advanced Data Analytics in Health
Advanced Data Analytics in Health[electronic resource] /edited by Philippe J. Giabbanelli, Vijay K. Mago, Elpiniki I. Papageorgiou. - 1st ed. 2018. - XIV, 216 p.online resource. - Smart Innovation, Systems and Technologies,932190-3018 ;. - Smart Innovation, Systems and Technologies,37.

Dimensionality 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.

This 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.

ISBN: 9783319779119

Standard No.: 10.1007/978-3-319-77911-9doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Advanced Data Analytics in Health
LDR:02934nam a22004095i 4500 001 992173
003 DE-He213
005 20200703125819.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319779119 $9 978-3-319-77911-9
024 7 $a 10.1007/978-3-319-77911-9 $2 doi
035 $a 978-3-319-77911-9
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Advanced Data Analytics in Health $h [electronic resource] / $c edited by Philippe J. Giabbanelli, Vijay K. Mago, Elpiniki I. Papageorgiou.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a XIV, 216 p. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Smart Innovation, Systems and Technologies, $x 2190-3018 ; $v 93
505 0 $a Dimensionality 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.
520 $a This 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.
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 0 $a Health informatics. $3 1064466
650 0 $a Big data. $3 981821
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Health Informatics. $3 593963
650 2 4 $a Big Data/Analytics. $3 1106909
700 1 $a Giabbanelli, Philippe J. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1203750
700 1 $a Mago, Vijay K. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1203751
700 1 $a Papageorgiou, Elpiniki I. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1023142
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319779102
776 0 8 $i Printed edition: $z 9783319779126
776 0 8 $i Printed edition: $z 9783030085711
830 0 $a Smart Innovation, Systems and Technologies, $x 2190-3018 ; $v 37 $3 1255196
856 4 0 $u https://doi.org/10.1007/978-3-319-77911-9
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)