000 | 03798nam a22005895i 4500 | ||
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001 | 978-3-319-77911-9 | ||
003 | DE-He213 | ||
005 | 20220801215823.0 | ||
007 | cr nn 008mamaa | ||
008 | 180420s2018 sz | s |||| 0|eng d | ||
020 |
_a9783319779119 _9978-3-319-77911-9 |
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024 | 7 |
_a10.1007/978-3-319-77911-9 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
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072 | 7 |
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_a006.3 _223 |
245 | 1 | 0 |
_aAdvanced Data Analytics in Health _h[electronic resource] / _cedited by Philippe J. Giabbanelli, Vijay K. Mago, Elpiniki I. Papageorgiou. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
|
300 |
_aXIV, 216 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSmart Innovation, Systems and Technologies, _x2190-3026 ; _v93 |
|
505 | 0 | _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. | |
520 | _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. | ||
650 | 0 |
_aComputational intelligence. _97716 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aMedical informatics. _94729 |
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650 | 0 |
_aQuantitative research. _94633 |
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650 | 1 | 4 |
_aComputational Intelligence. _97716 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aHealth Informatics. _931799 |
650 | 2 | 4 |
_aData Analysis and Big Data. _946647 |
700 | 1 |
_aGiabbanelli, Philippe J. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _946648 |
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700 | 1 |
_aMago, Vijay K. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _946649 |
|
700 | 1 |
_aPapageorgiou, Elpiniki I. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _946650 |
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710 | 2 |
_aSpringerLink (Online service) _946651 |
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_iPrinted edition: _z9783319779102 |
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_iPrinted edition: _z9783319779126 |
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_iPrinted edition: _z9783030085711 |
830 | 0 |
_aSmart Innovation, Systems and Technologies, _x2190-3026 ; _v93 _946652 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-77911-9 |
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