Use of artificial intelligence to shorten the behavioral diagnosis of autism

PLoS ONE

Volumn 7, Issue 8, 2012, Pages

  Wall, Dennis P ^a,b   Dally, Rebecca ^a   Luyster, Rhiannon ^c   Jung, Jae Yoon ^a   DeLuca, Todd F ^a  

^a Harvard Medical School Center for Biomedical Informatics   (United States)

^b BETH ISRAEL DEACONESS MEDICAL CENTER   (United States)

^c BOSTON CHILDREN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL INTELLIGENCE; AUTISM; AUTISM DIAGNOSTIC INTERVIEW REVISED; BEHAVIOR; CLASSIFIER; COMPUTER SIMULATION; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; MACHINE LEARNING; PSYCHOLOGIC TEST; SENSITIVITY AND SPECIFICITY;

ADOLESCENT; ADULT; ARTIFICIAL INTELLIGENCE; AUTISTIC DISORDER; BEHAVIOR; CASE-CONTROL STUDIES; CHILD; CHILD, PRESCHOOL; DECISION TREES; HUMANS; INFANT; INFANT, NEWBORN; MIDDLE AGED; QUESTIONNAIRES; RETROSPECTIVE STUDIES; TIME FACTORS; YOUNG ADULT;

EID: 84865428954     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0043855     Document Type: Article

References (42)

1. Bailey A, Le Couteur A, Gottesman I, Bolton P, Simonoff E, et al. (1995) Autism as a strongly genetic disorder: evidence from a British twin study. Psychol Med 25: 63-77.
2. Lord C, Rutter M, Le Couteur A, (1994) Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord 24: 659-685.
3. Cicchetti DV, Lord C, Koenig K, Klin A, Volkmar FR, (2008) Reliability of the ADI-R: multiple examiners evaluate a single case. J Autism Dev Disord 38: 764-770.
4. Poustka F, Lisch S, Ruhl D, Sacher A, Schmotzer G, et al. (1996) The standardized diagnosis of autism, Autism Diagnostic Interview-Revised: interrater reliability of the German form of the interview. Psychopathology 29: 145-153.
5. Hill A, Bolte S, Petrova G, Beltcheva D, Tacheva S, et al. (2001) Stability and interpersonal agreement of the interview-based diagnosis of autism. Psychopathology 34: 187-191.
6. Wiggins LD, Baio J, Rice C, (2006) Examination of the time between first evaluation and first autism spectrum diagnosis in a population-based sample. Journal of developmental and behavioral pediatrics: JDBP 27: S79-87.
7. Bernier R, Mao A, Yen J, (2010) Psychopathology, families, and culture: autism. Child Adolesc Psychiatr Clin N Am 19: 855-867.
8. Howlin P (1998) Children with Autism and Asperger's Syndrome: A Guide for Practitioners and Parents. Chichester, UK: Wiley.
9. Pinto-Martin JA, Young LM, Mandell DS, Poghosyan L, Giarelli E, et al. (2008) Screening strategies for autism spectrum disorders in pediatric primary care. J Dev Behav Pediatr 29: 345-350.
10. Lord C, Petkova E, Hus V, Gan W, Lu F, et al. (2012) A multisite study of the clinical diagnosis of different autism spectrum disorders. Arch Gen Psychiatry 69: 306-313.
11. Autworks channel website. Available: http://www.youtube.com/user/autworks- p/f. Accessed 2012 Aug 6.
12. Berument SK, Rutter M, Lord C, Pickles A, Bailey A, (1999) Autism screening questionnaire: diagnostic validity. Br J Psychiatry 175: 444-451.
13. Eaves LC, Wingert HD, Ho HH, Mickelson EC, (2006) Screening for autism spectrum disorders with the social communication questionnaire. J Dev Behav Pediatr 27: S95-S103.
14. Robins DL, Fein D, Barton ML, Green JA, (2001) The Modified Checklist for Autism in Toddlers: an initial study investigating the early detection of autism and pervasive developmental disorders. J Autism Dev Disord 31: 131-144.
15. Lord C, Rutter M, Goode S, Heemsbergen J, Jordan H, et al. (1989) Autism diagnostic observation schedule: a standardized observation of communicative and social behavior. J Autism Dev Disord 19: 185-212.
16. Gura GF, Champagne MT, Blood-Siegfried JE, (2011) Autism spectrum disorder screening in primary care. J Dev Behav Pediatr 32: 48-51.
17. Pisula E, (2003) Parents of children with autism: review of current research. Arch Psychiatry Psychother 5: 51-63.
18. Wall DP, Kosmiscki J, Deluca TF, Harstad L, Fusaro VA (2012) Use of machine learning to shorten observation-based screening and diagnosis of autism. Translational Psychiatry 2.
19. Warren Z, Vehorn A, Dohrmann E, Nicholson A, Sutcliffe JS, et al. (2012) Accuracy of phenotyping children with autism based on parent report: what specifically do we gain phenotyping "rapidly"? Autism Res 5: 31-38.
20. Aldridge FJ, Gibbs VM, Schmidhofer K, Williams M, (2012) Investigating the clinical usefulness of the Social Responsiveness Scale (SRS) in a tertiary level, autism spectrum disorder specific assessment clinic. J Autism Dev Disord 42: 294-300.
21. Schanding GT, Jr., Nowell KP, Goin-Kochel RP (2011) Utility of the Social Communication Questionnaire-Current and Social Responsiveness Scale as Teacher-Report Screening Tools for Autism Spectrum Disorders. J Autism Dev Disord.
22. Geschwind DH, Sowinski J, Lord C, Iversen P, Shestack J, et al. (2001) The autism genetic resource exchange: a resource for the study of autism and related neuropsychiatric conditions. American journal of human genetics 69: 463-466.
23. Kohavi R (1995) A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Mellish C, editor; Montreal. Morgan Kaufmann, Los Altos, CA. 1137-l.
24. Frank E, Hall M, Trigg L, Holmes G, Witten IH, (2004) Data mining in bioinformatics using Weka. Bioinformatics 20: 2479-2481.
25. Wilkinson DJ, (2007) Bayesian methods in bioinformatics and computational systems biology. Brief Bioinform 8: 109-116.
26. Fischbach GD, Lord C, (2010) The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron 68: 192-195.
27. Risi S, Lord C, Gotham K, Corsello C, Chrysler C, et al. (2006) Combining information from multiple sources in the diagnosis of autism spectrum disorders. Journal of the American Academy of Child and Adolescent Psychiatry 45: 1094-1103.
28. Weka Website. Available: http://www.cs.waikato.ac.nz/ml/weka/. Accessed 2012 Jun 14.
29. Freund Y, Mason L (1999) The alternating decision tree learning algorithm. 124-133.
30. Shi H (2007) Best-first Decision Tree Learning. Master Thesis, The University of Waikato.
31. Freund Y, Schapire RE (1996) Experiments with a new boosting algorithm. San Francisco. Morgan Kaufmann. 148-156.
32. Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, et al. (2009) The WEKA Data Mining Software: An Update. SIGKDD Explorations 11: 1.
33. Quinlan R (1993) C4.5. San Mateo: Morgan Kaufmann Publishers.
34. Freund Y, Mason L (1999) The alternating decision tree learning algorithm; San Francisco. 124-133.
35. Cohen WW (1995) Fast Effective Rule Induction. Twelfth International Conference on Machine Learning: 115-123.
36. Holmes G, Pfahringer B, Kirkby R, Frank E, Hall M (2001) Multiclass alternating decision trees. ECML: 161-172.
37. Martin B (1995) Instance-Based learning: Nearest Neighbor With Generalization. Hamilton, New Zealand.: University of Waikato. 33 p.
38. Holte RC, (1993) Very simple classification rules perform well on most commonly used datasets. Machine Learning: Proceedings of the Sixteenth International Conference 11: 63-91.
39. Frank E, Hall M (2001) A simple approach to ordinal prediction. European Conference on Machine Learning. Freiburg, Germany: Springer-Verlag. 145-156.
40. Frank E, Witten IH (1998) Generating Accurate Rule Sets Without Global Optimization. In: Shavlik J, editor; San Francisco, CA. Morgan Kaufmann Publishers.
41. Gaines BR, Compton P, (1995) Induction of Ripple-Down Rules Applied to Modeling Large Databases. J Intell Inf Syst 5: 211-228.
42. Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and Regression Trees. Wadsworth International Group, Belmont, California.