Personal Health Systems: Opportunities and Barriers for Adoption

Ilkka Korhonen; Elina M. Mattila; Mark van Gils

doi:10.1109/IEMBS.2010.5626309

Personal Health Systems: Opportunities and Barriers for Adoption

Ilkka Korhonen, Elina M. Mattila, Mark van Gils

VTT Technical Research Centre of Finland

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

2 Citations (Scopus)

Abstract

Objective and early detection of Alzheimer's disease (AD) is a demanding problem requiring consideration of manymodal 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 Engineering in Medicine and Biology
Publisher	IEEE Institute of Electrical and Electronic Engineers
ISBN (Print)	978-1-4244-4124-2, 978-1-4244-4123-5
DOIs	https://doi.org/10.1109/IEMBS.2010.5626309
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	Argentina
City	Buenos Aires
Period	31/08/10 → 4/09/10

Keywords

personal health systems
wellness
behavioral change
patient compliance

Access to Document

10.1109/IEMBS.2010.5626309

http://www.vtt.fi/inf/julkaisut/muut/2010/EMBC2010_Korhonen_et_al.pdf

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Cite this

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title = "Personal Health Systems: Opportunities and Barriers for Adoption",

abstract = "Objective and early detection of Alzheimer's disease (AD) is a demanding problem requiring consideration of manymodal 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 = "personal health systems, wellness, behavioral change, patient compliance",

author = "Ilkka Korhonen and Mattila, {Elina M.} and {van Gils}, Mark",

note = "Project code: 18982; 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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doi = "10.1109/IEMBS.2010.5626309",

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publisher = "IEEE Institute of Electrical and Electronic Engineers",

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Korhonen, I, Mattila, EM & van Gils, M 2010, Personal Health Systems: Opportunities and Barriers for Adoption. in Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE Institute of Electrical and Electronic Engineers, 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.2010.5626309

Personal Health Systems : Opportunities and Barriers for Adoption. / Korhonen, Ilkka; Mattila, Elina M.; van Gils, Mark.

Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE Institute of Electrical and Electronic Engineers, 2010.

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

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T1 - Personal Health Systems

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AU - Mattila, Elina M.

AU - van Gils, Mark

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PY - 2010

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N2 - Objective and early detection of Alzheimer's disease (AD) is a demanding problem requiring consideration of manymodal 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.

AB - Objective and early detection of Alzheimer's disease (AD) is a demanding problem requiring consideration of manymodal 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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KW - behavioral change

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SN - 978-1-4244-4123-5

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