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
"Sinopsis" puede pertenecer a otra edición de este libro.
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.
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
"Sobre este título" puede pertenecer a otra edición de este libro.
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Hardcover. Condición: new. Hardcover. 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 CenterOverall, 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 UniversityThe 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783031743825
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 660 pp. Englisch. Nº de ref. del artículo: 9783031743825
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