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Using Diagnostic Information to Develop a Machine Learning Application for the Effective Screening of Autism Spectrum Disorders

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Mental Health Informatics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 491))

Abstract

A 2-Class Support Vector Machine (SVM) classification model was developed by means of machine learning techniques and text analysis of Autism Spectrum Disorders (ASD) diagnostic reports. The ability of the 2-Class SVM application to screen for ASD is compared with other screening instruments: Gillian Autism Rating Scale—Second Edition [25], Social Communication Questionnaire [51] and Social Responsiveness Scale [11]. It was also cross-validated and refined based on a sample (n = 221). The classification performance of the SVM application was relatively better compared to the other instruments (accuracy = 83.7 %, precision = 98.8 %, sensitivity = 83.3 %, specificity = 88.9 %). A 1-Class SVM classification model was also described to highlight the usefulness of SVM with a skewed population.

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References

  1. Allen, C.W., Silove, N., William, K., Hutchins, P.: Validity if the social communication questionnaire in assessing risk of autism in preschool children with developmental problems. J. Autism Dev. Disord. 37, 1272–1278 (2007)

    Article  Google Scholar 

  2. Baird, G., Simonoff, E., Pickles, A., Chandler, S., Loucas, T., Meldrum, D.: Prevalence of disorders of the autism spectrum in a population cohort of children in South Thames: The special needs and autism project (SNAP). Lancet 368, 210–215 (2006)

    Article  Google Scholar 

  3. Beglinger, L.J., Smith, T.H.: A review of subtyping in autism and pro-posed dimensional classification model. J. Autism Dev. Disord. 31(4), 411–422 (2001)

    Article  Google Scholar 

  4. Berument, S.K., Rutter, M., Lord, C., Pickles, A., Bailey, A.: Autism screening questionnaire: Diagnostic validity. Br. J. Psychiatry. 175, 444–451 (1999)

    Article  Google Scholar 

  5. Bölte, S., Golan, O., Goodwin, M.S., Zwaigenbaum, L.: Editorial: What can innovative technologies do for autism spectrum disorders? Autism 14(3), 155–159 (2010)

    Article  Google Scholar 

  6. Centre for Disease Control: Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network. Morb. Mortal. Wkly. Rep. Surveill. Summ. 56, 1–28 (2007)

    Google Scholar 

  7. Chakrabarti, S., Fombonne, E.: Pervasive developmental disorders in preschool children: Confirmation of high prevalence. Am. J. Psychiarty. 162, 1133–1141 (2005)

    Article  Google Scholar 

  8. Chandler, S., Charman, T., Baird, G., Simonoff, E., Loucas, T., Meldrum, D.: Validation of the social communication questionnaire in a population cohort of children with autism spectrum disorder. J. Am. Acad. Child Adolesc. Psychiatry 46(10), 1324–1332 (2007)

    Article  Google Scholar 

  9. Charman, T., Baird, G.: Practitioner review: Diagnosis of autism spectrum disorders in 2- and 3-year-old children. J. Child Psychol. Psychiatry 43(3), 289–305 (2002)

    Article  Google Scholar 

  10. Charman, T., Baird, G., Simonoff, E., Loucas, T., Chandler, S., Meldrum, D.: Efficacy of three screening instruments in the identification of autistic spectrum disorder. Br. J. Psychiatry 191, 554–559 (2007)

    Article  Google Scholar 

  11. Constantino, J.N., Gruber, C.P.: Social Responsiveness Scale (SRS). Western Psychological Services, Los Angeles (2005)

    Google Scholar 

  12. Constantino, J.N., Gruber, C.P., Davis, S., Hayes, S., Passanante, N., Przybeck, T.: The factor structure of autistic traits. J. Child Psychol. Psychiatry 45(4), 719–726 (2004)

    Article  Google Scholar 

  13. Constantino, J.N., LaVesser, P.D., Zhang, Y., Abbacchi, A.G.T., Todd, R.D.: Rapid quantitative assessment of autistic social impairment by classroom teachers. J. Am. Acad. Child Adolesc. Psychiatry 46, 1668–1676 (2007)

    Article  Google Scholar 

  14. Corsello, C., Hus, V., Pickles, A., Risi, S., Cook, J.E.H., Leventhal, B.L.: Between a ROC and a hard place: Decision making and making decisions about using the SCQ. J. Child Psychol. Psychiatry. 48, 932–940 (2007)

    Article  Google Scholar 

  15. De bildt, A., Sytema, S., Ketelaars, C., Kraijer, D., Mulder, E., Volkmar, F.: Interrelationship between autism diagnostic observation schedule-generic (ADOS-G), autism diagnostic interview-revised (ADI-R), and the di-agnostic and statistical manual of mental disorders (DSM-IV-TR) classification in children and adolescents with mental retardation. J. Autism Dev. Disord. 34(2), 129–137 (2004)

    Google Scholar 

  16. Diederich, J., Al-Ajmi, A., Yellowlees, P.: Ex-ray: Data mining and mental health. Appl. Soft Comput. 7(3), 923–928 (2007)

    Article  Google Scholar 

  17. DiLavore, P.C., Lord, C., Rutter, M.: The pre-linguistic autism diagnostic observation schedule. J. Autism Dev. Disord. 25(4), 355–379 (1995)

    Article  Google Scholar 

  18. DSM-IV.: Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association (1994)

    Google Scholar 

  19. Eaves, L.C., Wingert, H., Ho, H.H.: Screening for autism. Autism 10, 229–242 (2006)

    Article  Google Scholar 

  20. Filipek, P.A., Accardo, P.J., Ashwal, S., Baranek, G.T., Cook, E.H., Dawson, G., Gordon, B., Gravel, J.S., Johnson, C.P., Kallen, R.J., Levy, S.E., Minshew, N.J., Ozonoff, S., Prizant, B.M., Rapin, I., Rogers, S.J., Stone, W.L., Teplin, S.W., Tuchman, R.F., Volkmar, F.R.: Practice parameter: Screening and diagnosis of autism. 55. First published

    Google Scholar 

  21. Filipek, P.A., Accardo, P.J., Baranek, G.T., Cook Jr, E.H., Dawson, G., Gordon, B., Gravel, J.S., Johnson, C.P., Kallen, R.J., Levy, S.E., Minshew, N.J., Prizant, B.M., Rapin, I., Rogers, S.J., Stone, W.L., Teplin, S., Tuchman, R.F., Volkmar, F.R.: The screening and diagnosis of autistic spectrum disorders. J. Autism Dev. Disord. 29(6), 439–484 (1999)

    Article  Google Scholar 

  22. Fombonne, E.: Epidemiological surveys of autism and other pervasive developmental disorders: An update. J. Autism Dev. Disord. 33(4), 365–381 (2003)

    Article  Google Scholar 

  23. Georgiades, S., Szatmari, P., Zwaigenbaum, L., Duku, E., Bryson, S., Roberts, W.: Structure of the autism symptom phenotype: A proposed multidimensional model. J. Am. Acad. Child Adolesc. Psychiatry 43(2), 188–196 (2007)

    Article  Google Scholar 

  24. Gilliam, J.E.: Gilliam Autism Rating Scale. PRO-ED, Austin (1995)

    Google Scholar 

  25. Gilliam, J.E.: Gilliam Autism Rating Scale–Second Edition. PRO-ED, Austin (2006)

    Google Scholar 

  26. Goin-Kochel, R.P., Cohen, R.: Screening cases within a statewide autism registry. Focus Autism Other Dev. Disabil. 23(3), 148–154 (2008)

    Article  Google Scholar 

  27. Goin-Kochel, R.P., Mackintosh, V., Myers, B.J.: How many doctors does it take to make an autism spectrum diagnosis? Autism 10, 439–451 (2006)

    Article  Google Scholar 

  28. Goodwin, M.S.: Enhancing and accelerating the pace of autism research and treatment: The promise of developing innovative technology. Focus Autism Other Dev. Disabil. 23, 125–128 (2008)

    Article  Google Scholar 

  29. Gotham, K., Risi, S., Dawson, G., Tager-Flusberg, H., Joseph, R., Carter, A.: A replication of the autism diagnostic observation schedule (ADOS) revised algorithm. J. Am. Acad. Child Adolesc. Psychiatry 47(6), 642–651 (2008)

    Article  Google Scholar 

  30. Gotham, K., Risi, S., Pickles, A.: The autism diagnostic observation schedule: Revised algorithm for improved diagnostic validity. J. Autism Dev. Disord. 37, 613–627 (2007)

    Article  Google Scholar 

  31. Gray, K.M., Tonge, B.J., Sweeney, D.J.: Using the autism diagnostic interview-revised and the autism diagnostic observation schedule with young children with developmental delay: Evaluating diagnostic validity. J. Autism Dev. Disord. 38, 657–667 (2008)

    Article  Google Scholar 

  32. Howlin, P., Moore, A.: Diagnosis of autism: A survey of over 1200 patients in the UK. Autism 1, 135–162 (1997)

    Article  Google Scholar 

  33. ICD10.: International Statistical Classification of Disease and Related Health. World Health Organization, Geneva (1992)

    Google Scholar 

  34. Ingram, D.G., Takahashi, T.N., Miles, J.H.: Defining autism subgroups: A taxometric solution. J. Autism Dev. Disord. 38, 950–960 (2008)

    Article  Google Scholar 

  35. Johnson, C.P., Myers, S.M., Lipkin, P.H., Cartwright, J.D., Desch, L.W., Duby, J.C., Elias, E.R., Levey, E.B., Liptak, G.S., Murphy, N.A., Tilton, A.H., Lollar, D., Macias, M., McPherson, M., Olson, D.G., Strickland, B., Skipper, S.M., Ackermann, J., Del Monte, M., Challman, T.D., Hyman, S.L., Levy, S.E., Spooner, S.A., Yeargin-Allsopp, M.: Identification and evaluation of children with autism spectrum disorders. Pediatrics 120(5), 1183–1215 (2007)

    Article  Google Scholar 

  36. Johnson, C.P., Myers, S.M.: Identification and evaluation of children with autism spectrum disorders. Pediatrics 120, 1183–1215 (2007)

    Article  Google Scholar 

  37. Kabot, S., Masi, W., Segal, M.: Advances in the diagnosis and treatment of autism spectrum disorders. Prof. Psychol. Res. Pract. 34(1), 26–33 (2003)

    Article  Google Scholar 

  38. Klin, A., Lang, J., Cicchetti, D.V., Volkmar, F.R.: Brief report: Interrater reliability of clinical diagnosis and DSM-IV criteria for autistic disorder: Results of the DSM-IV autism field trial. J. Autism Dev. Disord. 30(2), 163–167 (2000)

    Article  Google Scholar 

  39. Lecavalier, L.: An evaluation of the Gilliam autism rating scale. J. Autism Dev. Disord. 35(6), 795–805 (2005)

    Article  Google Scholar 

  40. Lecavalier, L., Aman, M.G., Scahill, L., McDougle, C.J., McCracken, J.T., Vitiello, B.: Validity of the autism diagnostic interview-revised. Am. J. Ment. Retard. 111(3), 199–215 (2006)

    Article  Google Scholar 

  41. Lord, C., Luyster, R.: Early diagnosis of children with autism spectrum disorders. Clin. Neurosci. Res. 6, 189–194 (2006)

    Article  Google Scholar 

  42. Lord, C., Risi, S., Lambrecht, L., Cook, E.H., Leventhal, B.L., DiLavore, P.C.: The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism. J. Autism Dev. Disord. 30(3), 205–223 (2000)

    Article  Google Scholar 

  43. Lord, C., Risis, S.: Frameworks and methods in diagnosing autism spectrum disorders. Ment. Retard. Dev. Disabil. Res. Rev. 4, 90–96 (1998)

    Article  Google Scholar 

  44. Lord, C., Rutter, M., DiLavore, P.C., Risi, S.: Autism Diagnostic Observation Schedule. Western Psychological Services, Los Angeles (2002)

    Google Scholar 

  45. Mazefsky, C.A., Oswald, D.P.: The discriminative ability and diagnostic utility of the ADOS-G, ADI-R, and GARS for children in a clinical setting. Autism 10, 533–549 (2006)

    Article  Google Scholar 

  46. Norris, M., Lecavalier, L.: Screening accuracy of level 2 autism spectrum disorder rating scales: A review of selected instruments. Autism 14(4), 263–284 (2010)

    Article  Google Scholar 

  47. Noterdame, M., Mildenberger, K., Sitter, S.H.A.: Parent information and direct observation in the diagnosis of pervasive and specific develop-mental disorders. Autism 6(2), 159–168 (2002)

    Article  Google Scholar 

  48. Oosterling, I.J., Swinkels, S.H., Van der Gaag, R.J., Visser, J.C., Dietz, C., Buitelaar, J.K.: Comparative analysis of three screening instruments for autism spectrum disorders in toddlers at high risk. J. Autism Dev. Disord. 39, 897–909 (2009)

    Article  Google Scholar 

  49. Prior, M., Eisenmajer, R., Leekam, S., Wing, L., Gould, J., Ong, B.: Are there subgroups within the autistic spectrum? A cluster analysis of a group of children with autistic spectrum disorders. J. Child Psychol. Psychiatry 39(6), 893–902 (1998)

    Article  Google Scholar 

  50. Rosenberg, R.E., Daniels, A.M., Law, J.K., Law, P.A., Kaufmann, W.E.: Trends in autism spectrum disorder diagnoses: 1994–2007. J. Autism Dev. Disord. 39, 1099–1111 (2009)

    Article  Google Scholar 

  51. Rutter, M., Bailey, A., Lord, C.: Social Communication Questionnaire. Western Psychological Services, Los Angeles (2003)

    Google Scholar 

  52. Rutter, M., Le Couteur, A., Lord, C.: Autism Diagnostic Interview-Revised. Western Psychological Services, Los Angeles (2003)

    Google Scholar 

  53. Saracino, J., Noseworthy, J., Steiman, M., Reisinger, L., Fombonne, E.: Diagnostic and assessment issues in autism surveillance and prevalence. J. Dev. Phys. Disabil. 22, 317–330 (2010)

    Article  Google Scholar 

  54. Scahill, L.: Diagnosis and evaluation of pervasive developmental disorders. J. Clin. Psychiatry 66, 19–25 (2005)

    Google Scholar 

  55. Skellern, C., Schluter, P., McDowell, M.: From complexity to category: Responding to diagnostic uncertainties of autistic spectrum disorders. J. Paediatr. Child Health 41, 407–412 (2005)

    Article  Google Scholar 

  56. South, M., Williams, B.J., McMahon, W.M., Owley, T., Filipek, P.A., Shernoff, E.: Utility of the Gilliam autism rating scale in research and clinical populations. J. Autism Dev. Disord. 32, 593–599 (2002)

    Article  Google Scholar 

  57. Tadevosyan-Leyer, O., Dowd, M., Mankoski, R., Winklosy, B., Putnam, S., Mcgrath, L.: A principal components analysis of the autism diagnostic interview-revised. J. Am. Acad. Child Adolesc. Psychiatry 42(7), 864–872 (2003)

    Article  Google Scholar 

  58. Volkmar, F.R., State, M., Klin, A.: Autism and autism spectrum disorders: Diagnostic issues for the coming decade. J. Child Psychol. Psychiatry 50, 108–115 (2009)

    Article  Google Scholar 

  59. Wazana, A., Bresnahan, M., Kline, J.: The autism epidemic: Fact or artefact? J. Am. Acad. Child Adolesc. Psychiatry 43(6), 721–730 (2007)

    Article  Google Scholar 

  60. Williams, M.E., Atkins, M.T.S.: Assessment of autism in community settings: Discrepancies in classification. J. Autism Dev. Disord. 39(4), 660–669 (2008)

    Article  Google Scholar 

  61. Wing, L., Gould, J.: Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. J. Autism Dev. Disord. 9(1), 11–29 (1979)

    Article  Google Scholar 

  62. Witwer, A.N., Lecavalier, L.: Autism screening tools: An evaluation of the social communication questionnaire and the developmental behaviour checklist-autism screening algorithm. J. Intell. Dev. Disabil. 32(3), 179–187 (2007)

    Article  Google Scholar 

  63. World Health Organisation: The ICD-10 classification of mental and behavioural disorders: Clinical descriptions and diagnostic guidelines. World Health Organization, Geneva (1992)

    Google Scholar 

  64. Young, R.L., Brewer, N., Pattison, C.: Parental identification of early behavioural abnormalities in children with autistic disorder. Autism 7(2), 125–143 (2003)

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute of Mental Health, Singapore, Singapore

    Tze Jui Goh & Min Sung

  2. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Q4072, Australia

    Joachim Diederich

  3. School of Business and IT, James Cook University, Singapore Campus, Singapore, 574421, Singapore

    Insu Song

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  1. Tze Jui Goh
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  2. Joachim Diederich
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  3. Insu Song
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  4. Min Sung
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Correspondence to Tze Jui Goh .

Editor information

Editors and Affiliations

  1. Computer Engineering, RMIT University School of Electrical and, Melbourne, Victoria, Australia

    Margaret Lech

  2. Singapore Campus, James Cook University Australia, School of Business and IT, Singapore, Singapore

    Insu Song

  3. Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento, California, USA

    Peter Yellowlees

  4. Psychology Network Pty Ltd, Brisbane, Australia

    Joachim Diederich

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Goh, T.J., Diederich, J., Song, I., Sung, M. (2014). Using Diagnostic Information to Develop a Machine Learning Application for the Effective Screening of Autism Spectrum Disorders. In: Lech, M., Song, I., Yellowlees, P., Diederich, J. (eds) Mental Health Informatics. Studies in Computational Intelligence, vol 491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38550-6_13

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  • DOI: https://doi.org/10.1007/978-3-642-38550-6_13

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