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[null,null,"Autore",null,"Boland Mary Regina"]
[null,null,"Titolo",null,"Health Analytics with R : Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics / / by Mary Regina Boland"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9783031743832"]
[{"$nulls":4},"3031743830"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (663 pages)"]
[null,null,"Disciplina",null,"570.28"]
[{"$nulls":4},"572.865"]
[null,null,"Soggetti",null,"Biology - Technique"]
[{"$nulls":4},"Gene expression"]
[{"$nulls":4},"Quantitative research"]
[{"$nulls":4},"Genetics"]
[{"$nulls":4},"Genomics"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[{"$nulls":4},"Gene Expression Analysis"]
[{"$nulls":4},"Data Analysis and Big Data"]
[{"$nulls":4},"Biological Techniques"]
[{"$nulls":4},"Genomic Analysis"]
[{"$nulls":4},"Data Science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Chapter 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 "]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","This 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."]