Network-guided group feature selection for classification of autism spectrum disorder

Veronika Cheplygina; David M.J. Tax; Marco Loog; Aasa Feragen

doi:10.1007/978-3-319-10581-9_24

Network-guided group feature selection for classification of autism spectrum disorder

Veronika Cheplygina, David M.J. Tax, Marco Loog, Aasa Feragen

3 Citations (Scopus)

Abstract

We present an anatomically guided feature selection scheme for prediction of neurological disorders based on brain connectivity networks. Using anatomical information not only gives rise to an interpretable model, but also prevents overfitting, caused by high dimensionality, noise and correlated features. Our method selects meaningful and discriminative groups of connections between anatomical regions, which can be used as input for any supervised classifier, such as logistic regression or a support vector machine. We demonstrate the effectiveness of our method on a dataset of autism spectrum disorder, with an AUC of 0.76, outperforming baseline methods.

Original language	English
Title of host publication	Machine learning in medical imaging : 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings
Editors	Guorong Wu, Daoqiang Zhang, Luping Zhou
Number of pages	8
Publisher	Springer
Publication date	2014
Pages	190-197
Chapter	24
ISBN (Print)	978-3-319-10580-2
ISBN (Electronic)	978-3-319-10581-9
DOIs	https://doi.org/10.1007/978-3-319-10581-9_24
Publication status	Published - 2014
Event	5th International Workshop on Machine Learning in Medical Imaging - Boston, United States Duration: 14 Sept 2014 → 14 Sept 2014 Conference number: 5

Conference

Conference	5th International Workshop on Machine Learning in Medical Imaging
Number	5
Country/Territory	United States
City	Boston
Period	14/09/2014 → 14/09/2014

Series	Lecture notes in computer science
Volume	8679
ISSN	0302-9743

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10.1007/978-3-319-10581-9_24

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Cheplygina, V., Tax, D. M. J., Loog, M., & Feragen, A. (2014). Network-guided group feature selection for classification of autism spectrum disorder. In G. Wu, D. Zhang, & L. Zhou (Eds.), Machine learning in medical imaging: 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings (pp. 190-197). Springer. Lecture notes in computer science Vol. 8679 https://doi.org/10.1007/978-3-319-10581-9_24

Network-guided group feature selection for classification of autism spectrum disorder. / Cheplygina, Veronika; Tax, David M.J.; Loog, Marco et al.

Machine learning in medical imaging: 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings. ed. / Guorong Wu; Daoqiang Zhang; Luping Zhou. Springer, 2014. p. 190-197 (Lecture notes in computer science, Vol. 8679).

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

Cheplygina, V, Tax, DMJ, Loog, M & Feragen, A 2014, Network-guided group feature selection for classification of autism spectrum disorder. in G Wu, D Zhang & L Zhou (eds), Machine learning in medical imaging: 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings. Springer, Lecture notes in computer science, vol. 8679, pp. 190-197, 5th International Workshop on Machine Learning in Medical Imaging, Boston, United States, 14/09/2014. https://doi.org/10.1007/978-3-319-10581-9_24

Cheplygina V, Tax DMJ, Loog M, Feragen A. Network-guided group feature selection for classification of autism spectrum disorder. In Wu G, Zhang D, Zhou L, editors, Machine learning in medical imaging: 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings. Springer. 2014. p. 190-197. (Lecture notes in computer science, Vol. 8679). doi: 10.1007/978-3-319-10581-9_24

Cheplygina, Veronika ; Tax, David M.J. ; Loog, Marco et al. / Network-guided group feature selection for classification of autism spectrum disorder. Machine learning in medical imaging: 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings. editor / Guorong Wu ; Daoqiang Zhang ; Luping Zhou. Springer, 2014. pp. 190-197 (Lecture notes in computer science, Vol. 8679).

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Network-guided group feature selection for classification of autism spectrum disorder

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