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

doi:10.1109/IEMBS.2010.5626311

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 proceeding › Conference article in proceedings › Scientific › peer-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 language	English
Title of host publication	Proceedings of the 32nd Annual International Conference of the IEEE EMBS 2010
Place of Publication	Piscataway
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	2886-2889
ISBN (Print)	978-1-4244-4124-2, 978-1-4244-4123-5
DOIs	https://doi.org/10.1109/IEMBS.2010.5626311
Publication status	Published - 2010
MoE publication type	A4 Article in a conference publication
Event	32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina Duration: 31 Aug 2010 → 4 Sep 2010

Conference

Conference	32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Abbreviated title	EMBC'10
Country/Territory	Argentina
City	Buenos Aires
Period	31/08/10 → 4/09/10

Keywords

Alzheimer`s disease
feature selection
decision support
classification
data mining

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10.1109/IEMBS.2010.5626311

https://publications.vtt.fi/julkaisut/muut/2010/vanGils_EMBEC2010.pdf

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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

van Gils, Mark ; Koikkalainen, Juha ; Mattila, Jussi ; Herukka, Sanna-Kaisa ; Lötjönen, Jyrki ; Soininen, Hilkka. / Discovery and use of efficient biomarkers for objective disease state assessment in Alzheimer's disease. Proceedings of the 32nd Annual International Conference of the IEEE EMBS 2010. Piscataway : IEEE Institute of Electrical and Electronic Engineers, 2010. pp. 2886-2889

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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.",

keywords = "Alzheimer`s disease, feature selection, decision support, classification, data mining",

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note = "Project code: 18493; 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, EMBC'10 ; Conference date: 31-08-2010 Through 04-09-2010",

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language = "English",

isbn = "978-1-4244-4124-2",

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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. IEEE Institute of Electrical and Electronic Engineers, Piscataway, pp. 2886-2889, 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, Buenos Aires, Argentina, 31/08/10. https://doi.org/10.1109/IEMBS.2010.5626311

Discovery and use of efficient biomarkers for objective disease state assessment in Alzheimer's disease. / van Gils, Mark; Koikkalainen, Juha; Mattila, Jussi; Herukka, Sanna-Kaisa; Lötjönen, Jyrki; Soininen, Hilkka.

Proceedings of the 32nd Annual International Conference of the IEEE EMBS 2010. Piscataway : IEEE Institute of Electrical and Electronic Engineers, 2010. p. 2886-2889.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Lötjönen, Jyrki

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AB - 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.

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van Gils M, Koikkalainen J, Mattila J, Herukka S-K, Lötjönen J, Soininen H. 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. Piscataway: IEEE Institute of Electrical and Electronic Engineers. 2010. p. 2886-2889 https://doi.org/10.1109/IEMBS.2010.5626311

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

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Keywords

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