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Resources for Studying Statistical Analysis of Biomedical Data and R

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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8401))

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Abstract

The past decade has seen explosive growth in digitized medical data. This trend offers medical practitioners an unparalleled opportunity to identify effectiveness of treatments for patients using summary statistics and to offer patients more personalized medical treatments based on predictive analytics. To exploit this opportunity, statisticians and computer scientists need to work and communicate effectively with medical practitioners to ensure proper measurement data, collection of sufficient volumes of heterogeneous data to ensure patient privacy, and understanding of probabilities and sources of errors associated with data sampling. Interdisciplinary collaborations between scientists are likely to lead to the development of more effective methods for explaining probabilities, possible errors, and risks associated with treatment options to patients. This chapter introduces some online resources to help medical practitioners with little or no background in summary and predictive statistics learn basic statistical concepts and implement data analysis on their personal computers using R, a high-level computer language that requires relatively little training. Readers who are only interested in understanding basic statistical concepts may want to skip the subsection on R.

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Author information

Authors and Affiliations

  1. IBM Research-Tokyo, 5-6-52 Toyosu, Koto-ku, Tokyo, 135-8511, Japan

    Mei Kobayashi

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  1. Mei Kobayashi
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Editors and Affiliations

  1. Research Unit Human-Computer Interaction, Austrian IBM Watson Think Gruop, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2/V, 8036, Graz, Austria

    Andreas Holzinger

  2. IBM Life Sciences Discovery Centre, TECHNA for the Advancement of Technology for Health, Princess Margaret Cancer Centre, University Health Network, TMDT Room 11-314, 101 College Street, M5G 1L7, Toronto, ON, Canada

    Igor Jurisica

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Kobayashi, M. (2014). Resources for Studying Statistical Analysis of Biomedical Data and R. In: Holzinger, A., Jurisica, I. (eds) Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. Lecture Notes in Computer Science, vol 8401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43968-5_10

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  • DOI: https://doi.org/10.1007/978-3-662-43968-5_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43967-8

  • Online ISBN: 978-3-662-43968-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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