Free Ebook R for Medicine and Biology (Jones and Bartlett Series in Biomedical Informatics), by Paul D. Lewis
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R for Medicine and Biology (Jones and Bartlett Series in Biomedical Informatics), by Paul D. Lewis
Free Ebook R for Medicine and Biology (Jones and Bartlett Series in Biomedical Informatics), by Paul D. Lewis
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R is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment. Introductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming language using numerous worked examples. Later chapters outline how R can be used, not just for biomedical data analysis, but also as an environment for the processing, storing, reporting, and sharing of data and results. The remainder of the book explores areas of R application to common domains of biomedical informatics, including imaging, statistical analysis, data mining/modeling, pathology informatics, epidemiology, clinical trials, and metadata usage. R for Medicine and Biology will provide you with a single desk reference for the R environment and its many capabilities.
- Sales Rank: #357669 in Books
- Published on: 2009-05-22
- Original language: English
- Number of items: 1
- Dimensions: 9.90" h x .90" w x 7.00" l, 1.65 pounds
- Binding: Paperback
- 399 pages
Most helpful customer reviews
0 of 0 people found the following review helpful.
Very good!
By Dave C.
I've owned a few instructional R books. This one is good. This books takes the approach of teaching by example rather than by lengthy descriptions and explanations. For instance, after you briefly read about what "tapply" does and then try the example provided in the book you will most likely understand how to use "tapply" if you don't already know. Or you can read some lengthy description of "tapply" on the web and not really understand what its saying. Lots of biomedical examples and a good sampling of advanced approaches make this book a worthwhile purchase.
Why 4 stars? Data sets mentioned throughout the book are no longer available at the book's companion website. There is a data set folder but some of the data sets are not in there. This has been somewhat frustrating.
2 of 3 people found the following review helpful.
There are better books out there
By Charles
Poorly conceived book. The page count is misleading, with normal formatting the page count would easily be � of what is listed on amazon. It would be a challenge to just provide a brief introduction to the R program given that page limitation. Yet in the space available, the author tries to cover everything from a general introduction to survival analysis, fMRI data and machine learning using R. The result is that there are essentially 5 pages given to each of these fairly complex topic - not enough to be useful in any meaningful way. A good introduction to R (the R book, R in action etc) and an area specific book or google search will serve you much better than purchasing a single book like this.
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