The first edition of the textbook Data Science and Predictive Analytics: Biomedical and Health Applications using R, authored by Ivo D. Dinov, was published in August 2018 by Springer.[1] The second edition of the book was printed in 2023.[2]
This textbook covers some of the core mathematical foundations, computational techniques, and artificial intelligence approaches used in data science research and applications.[3]
By using the statistical computing platform R and a broad range of biomedical case-studies, the 23 chapters of the book first edition provide explicit examples of importing, exporting, processing, modeling, visualizing, and interpreting large, multivariate, incomplete, heterogeneous, longitudinal, and incomplete datasets (big data).[4]
^Dinov, Ivo (2018). Data Science and Predictive Analytics: Biomedical and Health Applications Using R. Springer.
^Dinov, Ivo (2023). Data Science and Predictive Analytics: Biomedical and Health Applications Using R. The Springer Series in Applied Machine Learning. Springer. doi:10.1007/978-3-031-17483-4. ISBN 978-3-031-17482-7. S2CID 256875731.
^Capaldi, Mindy (April 2019) [5 April 2019]. "(Review) Data Science and Predictive Analytics: Biomedical and Health Applications Using R". International Statistical Review. 87 (1): 181–182. doi:10.1111/insr.12317. S2CID 132379032.
^Saracco, Benjamin (2020) [April 2020]. "Review of Data Science and Predictive Analytics: Biomedical and Health Applications Using R". Journal of the Medical Library Association. 108 (2): 344. doi:10.5195/jmla.2020.901. PMC 7069824. S2CID 214729817.
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