000 04960nam a22006375i 4500
001 978-3-031-74383-2
003 DE-He213
005 20251030114652.0
007 cr nn 008mamaa
008 241231s2024 sz | s |||| 0|eng d
020 _a9783031743832
_9978-3-031-74383-2
024 7 _a10.1007/978-3-031-74383-2
_2doi
050 4 _aQH324
050 4 _aQH450-450.6
072 7 _aPSAK
_2bicssc
072 7 _aPDN
_2bicssc
072 7 _aSCI008000
_2bisacsh
072 7 _aPSAK
_2thema
072 7 _aPDN
_2thema
100 1 _aBoland, Mary Regina.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_989937
245 1 0 _aHealth Analytics with R
_h[electronic resource] :
_bLearning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics /
_cby Mary Regina Boland.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXVIII, 660 p. 193 illus., 145 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aChapter 1–Introduction -- Chapter 2-Genetics Analysis for Health Analytics -- Chapter 3-Determining Phenotypic Traits from Single Nucleotide Polymorphism (SNP) Data -- Chapter 4-Clinical Genetic Databases: ClinVar, ACMG Clinical Practice Guidelines -- Chapter 5-Inferring Disease Risk from Genetics -- Chapter 6-Challenges in Health Analytics Due to Lack of Diversity in Genetic Research: Implications and Issues with Published Knowledge -- Chapter 7-Clinical Data and Health Data Types -- Chapter 8-Clinical Datasets: Open Access Electronic Health Records Datasets -- Chapter 9-Association Mining with Clinical Data: Phenotype-Wide Association Studies (PheWAS) -- Chapter 10-Organizing a Clinical Study Across Multiple Clinical Systems: Common Data Models -- Chapter 11-Environmental Health Data Types for Health Analytics -- Chapter 12-Geospatial Analysis Using Environmental Health Data -- Chapter 13-Social Determinants of Health Data for Health Analytics -- Chapter 14-Geospatial Analysis Using Social Determinants of Health, Clinical Data and Spatial Regression Methods -- Chapter 15–Ethics.
520 _aThis textbook teaches health analytics using examples from the statistical programming language R. It utilizes real-world examples with publicly available datasets from healthcare and direct-to-consumer genetics to provide learners with real-world examples and enable them to get their hands on actual data. This textbook is designed to accompany either a senior-level undergraduate course or a Masters level graduate course on health analytics. The reader will advance from no prior knowledge of R to being well versed in applications within R that apply to data science and health analytics. “I have never seen a book like this and think it will make an important contribution to the field. I really like that it covers environmental, social, and geospatial data. I also really like the coverage of ethics. These aspects of health analytics are often overlooked or deemphasized. I will definitely buy copies for my team.” - Jason Moore, Cedars-Sinai Medical Center “Overall, I have a highly positive impression of the book. It is VERY comprehensive. It covers very extensive data types. I do not recall other books with the same level of comprehensiveness.” - Shuangge Ma, Yale University “The book is comprehensive in both aspects of genetics, and health analytics. It covers any type of information a healthcare data scientist should be familiar with, whether they are novice or experienced. I found any chapter that I looked into comprehensive, but also not too detailed (although in general this book is more than 600 pages of comprehensive and detailed relevant information).” - Robert Moskovtich, Ben-Gurion University of the Negev.
650 0 _aBiology
_xTechnique.
_967845
650 0 _aGene expression.
_977673
650 0 _aQuantitative research.
650 0 _aGenetics.
_968863
650 0 _aGenomics.
_964972
650 0 _aArtificial intelligence
_xData processing.
650 1 4 _aGene Expression Analysis.
_977674
650 2 4 _aData Analysis and Big Data.
650 2 4 _aGenetics.
_968863
650 2 4 _aBiological Techniques.
_967847
650 2 4 _aGenomic Analysis.
_978940
650 2 4 _aData Science.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031743825
776 0 8 _iPrinted edition:
_z9783031743849
776 0 8 _iPrinted edition:
_z9783031743856
856 4 0 _uhttps://doi.org/10.1007/978-3-031-74383-2
912 _aZDB-2-SME
912 _aZDB-2-SXM
999 _c66220
_d66220