Discovery and use of efficient biomarkers for objective disease state assessment in Alzheimer's disease

Mark van Gils, Juha Koikkalainen, Jussi Mattila, Sanna-Kaisa Herukka, Jyrki Lötjönen, Hilkka Soininen

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    8 Citations (Scopus)

    Abstract

    Objective and early detection of Alzheimer's disease (AD) is a demanding problem requiring consideration of many modal observations. Potentially, many features could be used to discern between people without AD and those at different stages of the disease. Such features include results from cognitive and memory tests, imaging (MRI, PET) results, cerebral spine fluid data, blood markers etc. However, in order to define an efficient and limited set of features that can be employed in classifiers requires mining of data from many patient cases. In this study we used two databases, ADNI and Kuopio LMCI, to investigate the relative importance of features and their combinations. Optimal feature combinations are to be used in a Clinical Decision Support System that is to be used in clinical AD diagnosis practice.
    Original languageEnglish
    Title of host publicationProceedings of the 32nd Annual International Conference of the IEEE EMBS 2010
    Place of PublicationPiscataway, NJ, USA
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages2886-2889
    ISBN (Print)978-1-4244-4124-2, 978-1-4244-4123-5
    DOIs
    Publication statusPublished - 2010
    MoE publication typeA4 Article in a conference publication
    Event32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
    Duration: 31 Aug 20104 Sep 2010

    Conference

    Conference32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    Abbreviated titleEMBC'10
    CountryArgentina
    CityBuenos Aires
    Period31/08/104/09/10

    Keywords

    • Alzheimer`s disease
    • feature selection
    • decision support
    • classification
    • data mining

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  • Cite this

    van Gils, M., Koikkalainen, J., Mattila, J., Herukka, S-K., Lötjönen, J., & Soininen, H. (2010). Discovery and use of efficient biomarkers for objective disease state assessment in Alzheimer's disease. In Proceedings of the 32nd Annual International Conference of the IEEE EMBS 2010 (pp. 2886-2889). IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/IEMBS.2010.5626311