R for Medicine and Biology

R for Medicine and Biology (Jones and Bartlett Series in Biomedical Informatics) [Paperback]

Author: Paul D. Lewis | Language: English | ISBN: 0763758086 | Format: PDF, EPUB

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R for Medicine and Biology
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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.

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• Paperback: 399 pages
• Publisher: Jones & Bartlett Learning; 1 edition (May 8, 2009)
• Language: English
• ISBN-10: 0763758086
• ISBN-13: 978-0763758080
• Product Dimensions: 9.8 x 7.1 x 0.8 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Amazon Best Sellers Rank: #1,624,198 in Books (See Top 100 in Books)
  • #86 in Books > Medical Books > Medicine > Prosthesis

Poorly conceived book. The page count is misleading, with normal formatting the page count would easily be ¼ 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.

By Charles

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