Wow! eBook
Health Analytics with R: Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics 2024th Edition
Author(s): Mary Regina Boland (Author)
- Publisher: Springer
- Publication Date: 1 Jan. 2025
- Edition: 2024th
- Language: English
- Print length: 678 pages
- ISBN-10: 3031743822
- ISBN-13: 9783031743825
Book Description
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
Editorial Reviews
From the Back Cover
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
About the Author
Dr. Mary Regina Boland has been in the field of informatics/health analytics for the past 14 years, specifically in academic medical centers for 13 years. She has taught a Precision Medicine/Health Analytics course for Masters-level students at the University of Pennsylvania for 5-years (2018-2023) located in Philadelphia, PA, USA, and she is currently teaching an advanced undergraduate level course called Health Analytics at Saint Vincent College in Latrobe, PA, USA.
