Feature selection and classification of imbalanced datasets. Application to PET images of children with autistic spectrum disorders

NeuroImage

Volumn 57, Issue 3, 2011, Pages 1003-1014

  Duchesnay, Edouard ^a,b,d   Cachia, Arnaud ^f   Boddaert, Nathalie ^c,d   Chabane, Nadia ^b,e   Mangin, Jean Franois ^a,b,d   Martinot, Jean Luc ^b,d   Brunelle, Francis ^c,d   Zilbovicius, Monica ^c,d  

^a NeuroSpin   (France)

^b DIF   (France)

^c HÔPITAL NECKER ENFANTS MALADES   (France)

^d Institut d'Imagerie Neurofonctionnelle (IFR 49)   (France)

^e ASSISTANCE PUBLIQUE HÔPITAUX DE PARIS   (France)

^f UNIVERSITÉ PARIS DESCARTES   (France)

Author keywords

Autism; Dimension reduction; Feature selection; Multivariate classification

Indexed keywords

ACCURACY; ARTICLE; AUTISM; BRAIN FUNCTION; BRAIN REGION; CHILD; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; CORRELATIONAL STUDY; FEMALE; HUMAN; IMAGE ANALYSIS; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL MODEL; NEUROIMAGING; PERFORMANCE MEASUREMENT SYSTEM; POSITRON EMISSION TOMOGRAPHY; PRESCHOOL CHILD; PRIORITY JOURNAL; SCHOOL CHILD; SENSITIVITY AND SPECIFICITY; SUPERIOR TEMPORAL SULCUS; TISSUE PERFUSION;

ADOLESCENT; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; BRAIN MAPPING; CHILD; CHILD DEVELOPMENT DISORDERS, PERVASIVE; CHILD, PRESCHOOL; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MALE; POSITRON-EMISSION TOMOGRAPHY;

EID: 79959747147     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.05.011     Document Type: Article

References (64)

1. Abell F., Krams M., Ashburner J., Passingham R., Friston K., Frackowiak R., Happé F., Frith C., Frith U. The neuroanatomy of autism: a voxel-based whole brain analysis of structural scans. Neuroreport 1999, 10(8):1647-1651. Jun.
2. Akaike H. A new look at the statistical model identification. IEEE Trans. Automatic Control 1974, 19(6):716-723.
3. Akshoomoff N., Lord C., Lincoln A.J., Courchesne R.Y., Carper R.A., Townsend J., Courchesne E. Outcome classification of preschool children with autism spectrum disorders using mri brain measures. J. Am. Acad. Child Adolesc. Psychiatry 2004, 43(3):349-357. Mar.
4. Alexander A.L., Lee J.E., Lazar M., Boudos R., DuBray M.B., Oakes T.R., Miller J.N., Lu J., Jeong E.-K., McMahon W.M., Bigler E.D., Lainhart J.E. Diffusion tensor imaging of the corpus callosum in autism. Neuroimage 2007, 34(1):61-73. Jan, URL. http://dx.doi.org/10.1016/j.neuroimage.2006.08.032.
5. Ambroise C., McLachlan G.J. Selection bias in gene extraction on the basis of microarray gene-expression data. Proc. Natl. Acad. Sci. U. S. A. 2002, 99(10):6562-6566. May, URL. http://dx.doi.org/10.1073/pnas.102102699.
6. APA Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR Text Revision 2000, American Psychiatric Publishing, Inc.
7. Aylward E.H., Minshew N.J., Goldstein G., Honeycutt N.A., Augustine A.M., Yates K.O., Barta P.E., Pearlson G.D. Mri volumes of amygdala and hippocampus in non-mentally retarded autistic adolescents and adults. Neurology 1999, 53(9):2145-2150. Dec.
8. Barnea-Goraly N., Kwon H., Menon V., Eliez S., Lotspeich L., Reiss A.L. White matter structure in autism: preliminary evidence from diffusion tensor imaging. Biol. Psychiatry 2004, 55(3):323-326. Feb.
9. Baron-Cohen S., Ring H.A., Bullmore E.T., Wheelwright S., Ashwin C., Williams S.C. The amygdala theory of autism. Neurosci. Biobehav. Rev. 2000, 24(3):355-364. May.
10. Birgé L., Massart P. Minimal penalties for gaussian model selection. Probability Theory Relat. Fields 2007, 138:33-73.
11. Boddaert N., Chabane N., Belin P., Bourgeois M., Royer V., Barthelemy C., Mouren-Simeoni M.-C., Philippe A., Brunelle F., Samson Y., Zilbovicius M. Perception of complex sounds in autism: abnormal auditory cortical processing in children. Am. J. Psychiatry 2004, 161(11):2117-2120. Nov, URL. http://dx.doi.org/10.1176/appi.ajp.161.11.2117.
12. Breiman L. Random forests. Mach. Learn. 2001, 45:5-32.
13. Burnham K.P., Anderson D.R. Model Selection and Multi-Model Inference: A Practical Information-Theoretic Approach 2004, Springer-Verlag New York Inc.
14. Castelli F., Frith C., Happé F., Frith U. Autism, asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes. Brain 2002, 125(Pt 8):1839-1849. Aug.
15. Chang C.-C., Lin C.-J. LIBSVM: A Library for Support Vector Machines 2001, Software available at. http://www.csie.ntu.edu.tw/cjlin/libsvm.
16. Chawla N.V., Bowyer K.W., Moore T.E., Kegelmeyer P. Smote: synthetic minority over-sampling technique. J. Artif. Intell. Res. 2002, 16:321-357.
17. Chawla N., Japkowicz N., Kolcz A. Editorial: special issue on learning from imbalanced data sets. ACM SIGKDD Explorations 2004.
18. Courchesne E., Yeung-Courchesne R., Press G.A., Hesselink J.R., Jernigan T.L. Hypoplasia of cerebellar vermal lobules vi and vii in autism. N. Engl. J. Med. 1988, 318(21):1349-1354. May.
19. Dalton K.M., Nacewicz B.M., Johnstone T., Schaefer H.S., Gernsbacher M.A., Goldsmith H.H., Alexander A.L., Davidson R.J. Gaze fixation and the neural circuitry of face processing in autism. Nat. Neurosci. 2005, 8(4):519-526. Apr, URL. http://dx.doi.org/10.1038/nn1421.
20. Dapretto M., Davies M.S., Pfeifer J.H., Scott A.A., Sigman M., Bookheimer S.Y., Iacoboni M. Understanding emotions in others: mirror neuron dysfunction in children with autism spectrum disorders. Nat. Neurosci. 2006, 9(1):28-30. Jan, URL. http://dx.doi.org/10.1038/nn1611.
21. Dietterich T.G. Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput. 1998, 10:1895-1923.
22. Duchesnay E., Cachia A., Roche A., Rivière D., Cointepas Y., Papadopoulos-Orfanos D., Zilbovicius M., Martinot J.-L., Régis J., Mangin J.-F. Classification based on cortical folding patterns. IEEE Trans. Med. Imaging 2007, 26(4):553-565. Apr, URL. http://dx.doi.org/10.1109/TMI.2007.892501.
23. Ecker C., Marquand A., Mourã£o-Miranda J., Johnston P., Daly E.M., Brammer M.J., Maltezos S., Murphy C.M., Robertson D., Williams S.C., Murphy D.G.M. Describing the brain in autism in five dimensions-magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J. Neurosci. 2010, 30(32):10612-10623. Aug, URL. http://dx.doi.org/10.1523/JNEUROSCI.5413-09.2010.
24. Ecker C., Rocha-Rego V., Johnston P., Mourao-Miranda J., Marquand A., Daly E.M., Brammer M.J., Murphy C., Murphy D.G., Consortium M.R.C.A. Investigating the predictive value of whole-brain structural mr scans in autism: a pattern classification approach. Neuroimage 2010, 49(1):44-56. Jan, URL. http://dx.doi.org/10.1016/j.neuroimage.2009.08.024.
25. Egaas B., Courchesne E., Saitoh O. Reduced size of corpus callosum in autism. Arch. Neurol. 1995, 52(8):794-801. Aug.
26. Fan Y., Shen D., Gur R.C., Gur R.E., Davatzikos C. Compare: classification of morphological patterns using adaptive regional elements. IEEE Trans. Med. Imaging 2007, 26(1):93-105. Jan, URL. http://dx.doi.org/10.1109/TMI.2006.886812.
27. Friedman J.H., Hastie T., Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 2010, 33(1):1-22. URL. http://www.jstatsoft.org/v33/i01.
28. Friston K.J., Ashburner J., Frith C.D., Poline J.-B., Heather J.D., Frackowiak R.S.J. Spatial registration and normalization of images. Hum. Brain Mapp. 1995, 3:165-189.
29. Gervais H., Belin P., Boddaert N., Leboyer M., Coez A., Sfaello I., Barthélémy C., Brunelle F., Samson Y., Zilbovicius M. Abnormal cortical voice processing in autism. Nat. Neurosci. 2004, 7(8):801-802. Aug, URL. http://dx.doi.org/10.1038/nn1291.
30. Guyon I., Elisseeff A. An introduction to variable and feature selection. J. Mach. Learn. Res. 2003, 3:1157-1182.
31. Guyon I., Weston J., Barnhill S., Vapnik V. Gene selection for cancer classification using support vector machines. Mach. Learn. 2002, 46:389-422.
32. Guyon I., Gunn S., Nikravesh M., Zadeh L. Feature Extraction: Foundations and Applications 2006, Springer-Verlag.
33. Hadjikhani N., Joseph R.M., Snyder J., Chabris C.F., Clark J., Steele S., McGrath L., Vangel M., Aharon I., Feczko E., Harris G.J., Tager-Flusberg H. Activation of the fusiform gyrus when individuals with autism spectrum disorder view faces. Neuroimage 2004, 22(3):1141-1150. Jul, URL. http://dx.doi.org/10.1016/j.neuroimage.2004.03.025.
34. Hadjikhani N., Joseph R.M., Snyder J., Tager-Flusberg H. Anatomical differences in the mirror neuron system and social cognition network in autism. Cereb. Cortex 2006, 16(9):1276-1282. Sep, URL. http://dx.doi.org/10.1093/cercor/bhj069.
35. Hand D.J., Taylor C. Multivariate Analysis of Variance and Repeated Measures: A Practical Approach for Behavioural Scientists 1987, Chapman & Hall.
36. Haznedar M.M., Buchsbaum M.S., Metzger M., Solimando A., Spiegel-Cohen J., Hollander E. Anterior cingulate gyrus volume and glucose metabolism in autistic disorder. Am. J. Psychiatry 1997, 154(8):1047-1050. Aug.
37. Howard M.A., Cowell P.E., Boucher J., Broks P., Mayes A., Farrant A., Roberts N. Convergent neuroanatomical and behavioural evidence of an amygdala hypothesis of autism. Neuroreport 2000, 11(13):2931-2935. Sep.
38. Japkowicz N., Stephen S. The class imbalance problem: a systematic study. Intell. Data Anal. 2002, 6:429-449. October, URL. http://portal.acm.org/citation.cfm?id=1293951.1293954.
39. Ke X., Hong S., Tang T., Zou B., Li H., Hang Y., Zhou Z., Ruan Z., Lu Z., Tao G., Liu Y. Voxel-based morphometry study on brain structure in children with high-functioning autism. Neuroreport 2008, 19(9):921-925. Jun, URL. http://dx.doi.org/10.1097/WNR.0b013e328300edf3.
40. Keller T.A., Kana R.K., Just M.A. A developmental study of the structural integrity of white matter in autism. Neuroreport 2007, 18(1):23-27. Jan, URL. http://dx.doi.org/10.1097/01.wnr.0000239965.21685.99.
41. Klöppel S., Stonnington C.M., Chu C., Draganski B., Scahill R.I., Rohrer J.D., Fox N.C., Jack C.R., Ashburner J., Frackowiak R.S.J. Automatic classification of mr scans in alzheimer's disease. Brain 2008, 131(Pt 3):681-689. Mar, URL. http://dx.doi.org/10.1093/brain/awm319.
42. Kohavi R. A study of cross-validation and bootstrap for accuracy estimation and model selection. International Joint Conference on Artificial Intelligence 1995, 1137-1143. Morgan Kaufmann.
43. Kohavi R., John G. Wrappers for feature selection. Artif. Intell. 1997, 97:273-324.
44. Lord C., Leventhal B.L., Cook E.H. Quantifying the phenotype in autism spectrum disorders. Am. J. Med. Genet. 2001, 105(1):36-38. Jan.
45. Mason S.J., Graham N.E. Areas beneath the relative operating characteristics (roc) and relative operating levels (rol) curves: statistical significance and interpretation. Q. J. R. Meteorol. Soc. 2002, 128:2145-2166.
46. McAlonan G.M., Cheung V., Cheung C., Suckling J., Lam G.Y., Tai K.S., Yip L., Murphy D.G.M., Chua S.E. Mapping the brain in autism. a voxel-based mri study of volumetric differences and intercorrelations in autism. Brain 2005, 128(Pt 2):268-276. Feb, URL. http://dx.doi.org/10.1093/brain/awh332.
47. Müller R.-A., Cauich C., Rubio M.A., Mizuno A., Courchesne E. Abnormal activity patterns in premotor cortex during sequence learning in autistic patients. Biol. Psychiatry 2004, 56(5):323-332. Sep, URL. http://dx.doi.org/10.1016/j.biopsych.2004.06.007.
48. Neeley E.S., Bigler E.D., Krasny L., Ozonoff S., McMahon W., Lainhart J.E. Quantitative temporal lobe differences: autism distinguished from controls using classification and regression tree analysis. Brain Dev. 2007, 29(7):389-399. Aug, URL. http://dx.doi.org/10.1016/j.braindev.2006.11.006.
49. Ohnishi T., Matsuda H., Hashimoto T., Kunihiro T., Nishikawa M., Uema T., Sasaki M. Abnormal regional cerebral blood flow in childhood autism. Brain 2000, 123(Pt 9):1838-1844. Sep.
50. Osuna E.E., Freund R., Girosi F. Support Vector Machines: Training and Applications 1997, Tech. rep, MIT.
51. Pelphrey K.A., Morris J.P., McCarthy G. Neural basis of eye gaze processing deficits in autism. Brain 2005, 128(Pt 5):1038-1048. May, URL. http://dx.doi.org/10.1093/brain/awh404.
52. Pereira F., Mitchell T., Botvinick M. Machine learning classifiers and fmri: a tutorial overview. Neuroimage 2009, 45(Suppl. 1):S199-S209. Mar, URL. http://dx.doi.org/10.1016/j.neuroimage.2008.11.007.
53. Pierce K., Haist F., Sedaghat F., Courchesne E. The brain response to personally familiar faces in autism: findings of fusiform activity and beyond. Brain 2004, 127(Pt 12):2703-2716. Dec, URL. http://dx.doi.org/10.1093/brain/awh289.
54. Pudil P., Novovicov'a J., Kittle J. Floating search methods in feature selection. Pattern Recogn. Lett. 1994, 15:1119-1125.
55. Raskutti B., Kowalczyk A. Extreme re-balancing for svms: a case study. ACM SIGKDD Explorations Newsletter - Special Issue on Learning from Imbalanced Datasets 2004.
56. Reunanen J. Overfitting in making comparisons between variable selection methods. J. Mach. Learn. Res. 2003, 3:1371-1382.
57. Schultz R.T. Developmental deficits in social perception in autism: the role of the amygdala and fusiform face area. Int. J. Dev. Neurosci. 2005, 23(2-3):125-141. URL. http://dx.doi.org/10.1016/j.ijdevneu.2004.12.012.
58. Schwarz G. Estimating dimension of a model. Annu. Stat. 1978, 6:461-464.
59. Thirion B., Duchesnay E., Hubbard E., Dubois J., Poline J.-B., Lebihan D., Dehaene S. Inverse retinotopy: inferring the visual content of images from brain activation patterns. Neuroimage 2006, 33(4):1104-1116. Dec, URL. http://dx.doi.org/10.1016/j.neuroimage.2006.06.062.
60. Tibshirani R. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 1996, 58:267-288.
61. Veropoulos K., Campbell C., Cristianini N. Controlling the sensitivity of support vector machines. Proceedings of the International Joint Conference on AI 1999, 55-56.
62. Zhang J., Mani I. knn approach to unbalanced data distributions: a case study involving information extraction. Proceedings of the ICML'2003 Workshop on Learning from Imbalanced Datasets 2003.
63. Zilbovicius M., Garreau B., Tzourio N., Mazoyer B., Bruck B., Martinot J.L., Raynaud C., Samson Y., Syrota A., Lelord G. Regional cerebral blood flow in childhood autism: a spect study. Am. J. Psychiatry 1992, 149(7):924-930. Jul.
64. Zilbovicius M., Boddaert N., Belin P., Poline J.B., Remy P., Mangin J.F., Thivard L., Barthélémy C., Samson Y. Temporal lobe dysfunction in childhood autism: a pet study. positron emission tomography. Am. J. Psychiatry 2000, 157(12):1988-1993. Dec.