Boland

Health Analytics with R

Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics

Springer

ISBN 978-3-031-74382-5

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Bibliografische Daten

Fachbuch

Buch. Hardcover

2025

48 s/w-Abbildungen, 145 Farbabbildungen, Bibliographien.

In englischer Sprache

Umfang: xviii, 660 S.

Format (B x L): 15,5 x 23,5 cm

Verlag: Springer

ISBN: 978-3-031-74382-5

Produktbeschreibung

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

Autorinnen und Autoren

Kundeninformationen

Includes homework questions and a lab tutorial script that individuals can work through at the end of each chapter Links genetic data and other health datasets toward actionable insights in a step-by-step manner Connects DTC genetic data from 23andme and other DTC platforms to information about traits that have health implications

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