Cluster analysis of MR imaging in Alzheimer’s disease using decision tree refinement

A Hamou; Andrew Simmons; Michael  Bauer; Benoit Lewden; Yi  Zhang; Lars-Olof Wahlund; Eric Westman; Megan Pritchard; Iwona  Kloszewska; Patrizia Mecozzi; Hilkka Soininen; Magda Tsolaki; Bruno Vellas; Sebastian Muehlboeck; Alan Evans; Per Julin; Niclas Sjögren; Christian Spenger; Simon Lovestone; Femida Gwadry-Sridhar

Cluster analysis of MR imaging in Alzheimer’s disease using decision tree refinement

A Hamou, Andrew Simmons, Michael Bauer, Benoit Lewden, Yi Zhang, Lars-Olof Wahlund, Eric Westman, Megan Pritchard, Iwona Kloszewska, Patrizia Mecozzi, Hilkka Soininen, Magda Tsolaki, Bruno Vellas, Sebastian Muehlboeck, Alan Evans, Per Julin, Niclas Sjögren, Christian Spenger, Simon Lovestone, Femida Gwadry-Sridhar

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

The use of novel analytical techniques (such as data clustering and decision trees) that can model and predict patient disease outcomes has great potential for assessing disease process and progression in Alzheimer’s disease and mild cognitive impairment. For this study, 124 different variables (generated from image data, demographics and data) have been compiled and analyzed using a modified clustering algorithm. Our aim was to determine the influence of these variables on the incidence of Alzheimer’s and mild cognitive impairment. Furthermore, we used a decision tree algorithm to model the level of “importance” of variants influencing this decision.

Original language	English
Pages (from-to)	90-99
Number of pages	10
Journal	International Journal of Artifical Intelligence
Volume	6
Issue number	s11
Publication status	Published - Mar 2011

Keywords

Alzheimer's Disease, Mild Cognitive Impairment, Cluster Analysis, Decision Tree Analysis, MRI

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Hamou, A., Simmons, A., Bauer, M., Lewden, B., Zhang, Y., Wahlund, L.-O., Westman, E., Pritchard, M., Kloszewska, I., Mecozzi, P., Soininen, H., Tsolaki, M., Vellas, B., Muehlboeck, S., Evans, A., Julin, P., Sjögren, N., Spenger, C., Lovestone, S., & Gwadry-Sridhar, F. (2011). Cluster analysis of MR imaging in Alzheimer’s disease using decision tree refinement. International Journal of Artifical Intelligence, 6(s11), 90-99. http://www.ceser.in/ceserp/index.php/ijai/article/view/917

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title = "Cluster analysis of MR imaging in Alzheimer{\textquoteright}s disease using decision tree refinement",

abstract = "The use of novel analytical techniques (such as data clustering and decision trees) that can model and predict patient disease outcomes has great potential for assessing disease process and progression in Alzheimer{\textquoteright}s disease and mild cognitive impairment. For this study, 124 different variables (generated from image data, demographics and data) have been compiled and analyzed using a modified clustering algorithm. Our aim was to determine the influence of these variables on the incidence of Alzheimer{\textquoteright}s and mild cognitive impairment. Furthermore, we used a decision tree algorithm to model the level of “importance” of variants influencing this decision.",

keywords = "Alzheimer's Disease, Mild Cognitive Impairment, Cluster Analysis, Decision Tree Analysis, MRI",

author = "A Hamou and Andrew Simmons and Michael Bauer and Benoit Lewden and Yi Zhang and Lars-Olof Wahlund and Eric Westman and Megan Pritchard and Iwona Kloszewska and Patrizia Mecozzi and Hilkka Soininen and Magda Tsolaki and Bruno Vellas and Sebastian Muehlboeck and Alan Evans and Per Julin and Niclas Sj{\"o}gren and Christian Spenger and Simon Lovestone and Femida Gwadry-Sridhar",

year = "2011",

month = mar,

language = "English",

volume = "6",

pages = "90--99",

journal = "International Journal of Artifical Intelligence",

issn = "0974-0635",

publisher = "Indian Society for Development and Environment Research",

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Hamou, A, Simmons, A, Bauer, M, Lewden, B, Zhang, Y, Wahlund, L-O, Westman, E, Pritchard, M, Kloszewska, I, Mecozzi, P, Soininen, H, Tsolaki, M, Vellas, B, Muehlboeck, S, Evans, A, Julin, P, Sjögren, N, Spenger, C, Lovestone, S & Gwadry-Sridhar, F 2011, 'Cluster analysis of MR imaging in Alzheimer’s disease using decision tree refinement', International Journal of Artifical Intelligence, vol. 6, no. s11, pp. 90-99. <http://www.ceser.in/ceserp/index.php/ijai/article/view/917>

TY - JOUR

T1 - Cluster analysis of MR imaging in Alzheimer’s disease using decision tree refinement

AU - Hamou, A

AU - Simmons, Andrew

AU - Bauer, Michael

AU - Lewden, Benoit

AU - Zhang, Yi

AU - Wahlund, Lars-Olof

AU - Westman, Eric

AU - Pritchard, Megan

AU - Kloszewska, Iwona

AU - Mecozzi, Patrizia

AU - Soininen, Hilkka

AU - Tsolaki, Magda

AU - Vellas, Bruno

AU - Muehlboeck, Sebastian

AU - Evans, Alan

AU - Julin, Per

AU - Sjögren, Niclas

AU - Spenger, Christian

AU - Lovestone, Simon

AU - Gwadry-Sridhar, Femida

PY - 2011/3

Y1 - 2011/3

N2 - The use of novel analytical techniques (such as data clustering and decision trees) that can model and predict patient disease outcomes has great potential for assessing disease process and progression in Alzheimer’s disease and mild cognitive impairment. For this study, 124 different variables (generated from image data, demographics and data) have been compiled and analyzed using a modified clustering algorithm. Our aim was to determine the influence of these variables on the incidence of Alzheimer’s and mild cognitive impairment. Furthermore, we used a decision tree algorithm to model the level of “importance” of variants influencing this decision.

AB - The use of novel analytical techniques (such as data clustering and decision trees) that can model and predict patient disease outcomes has great potential for assessing disease process and progression in Alzheimer’s disease and mild cognitive impairment. For this study, 124 different variables (generated from image data, demographics and data) have been compiled and analyzed using a modified clustering algorithm. Our aim was to determine the influence of these variables on the incidence of Alzheimer’s and mild cognitive impairment. Furthermore, we used a decision tree algorithm to model the level of “importance” of variants influencing this decision.

KW - Alzheimer's Disease, Mild Cognitive Impairment, Cluster Analysis, Decision Tree Analysis, MRI

M3 - Article

SN - 0974-0635

VL - 6

SP - 90

EP - 99

JO - International Journal of Artifical Intelligence

JF - International Journal of Artifical Intelligence

IS - s11

ER -

Cluster analysis of MR imaging in Alzheimer’s disease using decision tree refinement

Abstract

Keywords

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