Health Analytics with R
Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics
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Beschreibung
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
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
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
Autor*in
Mary Regina Boland
Themen in »Health Analytics with R«
R directtoconsumer data science data analytics genetics health analytics Direct-to-consumer genetics R code data mining clinical data precision medicine personalized medicine