Introduction to Biomedical Data Science aims to fill the data science knowledge gap experienced by many clinical, administrative and technical staff. The textbook begins with an overview of what biomedical data science is and then embarks on a tour of topics beginning with spreadsheet tips and tricks and ending with artificial intelligence. In between, important topics are covered such as biostatistics, data visualization, database systems, big data, programming languages, bioinformatics, and machine learning. The textbook is available as a paperback and ebook. Visit the companion website at…mehr
Introduction to Biomedical Data Science aims to fill the data science knowledge gap experienced by many clinical, administrative and technical staff. The textbook begins with an overview of what biomedical data science is and then embarks on a tour of topics beginning with spreadsheet tips and tricks and ending with artificial intelligence. In between, important topics are covered such as biostatistics, data visualization, database systems, big data, programming languages, bioinformatics, and machine learning. The textbook is available as a paperback and ebook. Visit the companion website at https://www.informaticseducation.org for more information. Key features: Real healthcare datasets are used for examples and exercises; Knowledge of a programming language or higher math is not required; Multiple free or open source software programs are presented; YouTube videos are embedded in most chapters; Extensive resources chapter for further reading and learning; PowerPoints and an Instructor ManualHinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Robert E. Hoyt, MD, FACP, FAMIA, is an internal medicine physician who was in private practice for 15 years and served as a physician in the military for 20 years. During this time, he taught health informatics for 13 years at the University of West Florida. He has been involved in health informatics for the past two decades, but in the last five years, he has focused primarily on biomedical data science, with emphasis on machine learning and artificial intelligence. He is a co-author and co-editor of Health Informatics: Practical Guide that is in its seventh edition. Additionally, he is the co-editor and co-author of the Introduction to Biomedical Data Science with Robert Muenchen that launched in 2019. Robert A. Muenchen, MS, PSA, is the author of the BlueSky Statistics 7.1 User Guide, R for SAS and SPSS Users, and coauthor of R for Stata Users and Introduction to Biomedical Data Science. An ASA Accredited Professional Statistician, Bob wrote or co-authored over 70 articles published in scientific journals and conference proceedings. At the University of Tennessee, he guided more than 1,000 graduate theses and dissertations and he continues to teach R workshops there.
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