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Mass Spectrometry Diagnostic Software for Cancer Detection - Addressing Geographical Limitations

Martin Radlak and Ryszard Klempous

p. 395-404

    Abstract

    This paper presents steps required to detect a cancer disease based on data obtained from SELDI-TOF-MS. Here, the full process of detection : from raw data, through preprocessing towards classification has been outlined. Importantly, methods and algorithms are presented and described in terms of their usability. Moreover, based on the analysis software developed for the purpose of this work, comparison of classifiers performance based on preprocessing methods is conducted. Finally, guidelines for further research are indicated together with suggestions of how to apply the concept of 24/7 work organization to make the process of development and research faster.

    Index

    Keywords

    cancer detection, data analysis, 24h knowledge factory, diagnostic software, geographical collaboration

    Text

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    References

    Bibliographical reference

    Martin Radlak and Ryszard Klempous, « Mass Spectrometry Diagnostic Software for Cancer Detection - Addressing Geographical Limitations », CASYS, 21 | 2008, 395-404.

    Electronic reference

    Martin Radlak and Ryszard Klempous, « Mass Spectrometry Diagnostic Software for Cancer Detection - Addressing Geographical Limitations », CASYS [Online], 21 | 2008, Online since 13 September 2024, connection on 27 December 2024. URL : http://popups.uliege.be/3041-539x/index.php?id=3300

    Authors

    Martin Radlak

    School of Computer Science, University of Birmingham, Edgbaston, Bl5 2TT Birmingham,GB

    Ryszard Klempous

    Institute of Control and Optimization, Wroclaw University of Technology, ul. Wybrzee Wyspiaskiego 27, 50-370 Wroclaw, Poland

    By this author

    Copyright

    CC BY-SA 4.0 Deed