Abstract
Neurodevelopmental disorders in children like dyslexia and ADHD must be diagnosed at earlier stages as the children need to be provided with necessary aid. Comorbidity of dyslexia and ADHD is very high. Children with comorbidity of dyslexia and ADHD face comparatively more difficulty than children with just one of the disorders. Since all the three, dyslexia, ADHD and comorbid cases share many similar characteristics, it is hard to distinguish between cases which have only dyslexia or ADHD and those which have both. Manual analysis to differentiate based on standard scores of the psycho analysis tests provided inconsistent results. In this paper, we have applied standard machine learning techniques Random Forest, Support Vector Machine and Multilayer Perceptron to the diagnosis test results to classify between ADHD and comorbid cases, and dyslexia and comorbid cases. Analysis using the different individual psycho analysis tests is also done. Application of machine learning techniques provides better classification than the manual analysis.
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References
Eva, G., Antonella, G.M.D., Paolo, C.: Comorbidity of ADHD and dyslexia. Dev. Neuropsychol. 35(5), 475–493 (2010). https://doi.org/10.1080/87565641.2010.494748
Tager-Flusberg, H.: Neurodevelopmental Disorders. The MIT Press, Cambridge (1999)
Vellutino, F.R.: Dyslexia: Theory and Research. MIT Press, Cambridge (1979)
American Psychiatric Association: Diagnostic and Statistical Manual of Mental Diseases (DSM- V), 5th edn. American Psychiatric Publishing, Washington, DC (2013)
Willcutt, E.G., Pennington, B.F., Boada, R., Ogline, J.S., Tunick, R.A., Chhabildas, N.A., et al.: A comparison of the cognitive deficits in reading disability and attention deficit/hyperactivity disorder. J. Abnorm. Psychol. 110, 157–172 (2001)
Mental health problems in neurodevelopmental disorders. http://www.kcl.ac.uk/ioppn/depts/cap/research/MentalHealthProblemsinNeurodevelopmentalDisorders. Accessed 05 Feb 2020
Del’homme, M., Kim, T.S., Loo, S.K., Yang, M.H., Smalley, S.L.: Familiar association and frequency of learning disabilities in ADHD sibling pair families. J. Abnorm. Child Psychol. 35, 55–62 (2007)
Friedman, M.C., Chhabildas, N., Budhiraja, N., Willcutt, E.G., Pennington, B.F.: Etiology of the comorbidity between RD and ADHD: exploration of the non-random mating hypothesis. Am. J. Med. Genet. Part B, Neuropsychiatric Genet. 120, 109–115 (2003)
Gayan, J., Olson, R.K.: Genetic and environmental influences on orthographic and phonological skills in children with reading disabilities. Dev. Neuropsychol. 20, 483–507 (2001)
Willcutt, E.G., Pennington, B.F., DeFries, J.C.: A twin study of comorbidity between attention-deficit/hyper-activity disorder and reading disability. Am. J. Med. Genet. (Neuropsychiatrics Genetics) 96, 293–301 (2000)
Sanchez-Moran, M., Hernandez, J.A., Dunabeitia, J.A., Estevez, A., Barcena, L., Gonzalez-Lahera, A., et al.: Correction: Genetic association study of dyslexia and ADHD candidate genes in a Spanish cohort: implications of comorbid samples. PLoS ONE 13(12), e0209718 (2018). https://doi.org/10.1371/journal.pone.0209718
Marino, C., Giorda, R., Vanzin, L., Molteni, M., Lorusso, M.L., Nobile, M., et al.: No evidence for association and linkage disequilibrium between dyslexia and markers of four dopamine-related genes. Eur. Child Adolesc. Psychiatry 12, 198–202 (2003)
Langer, N., Benjamin, C., Becker, B.K.C., Gaab, N.: Comorbidity of reading disabilities and ADHD: Structural and functional brain characteristics. Hum. Brain Mapp. 40(9), 2677–2698 (2019). https://doi.org/10.1002/hbm.24552
McGrath, L.M., Stoodley, C.J.: Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies. J. Neurodevelopmental Disord. 11(31) (2019)
Debbie, G., Margaret, S., Charles, H.: Time perception, phonological skills and executive function in children with dyslexia and/or ADHD symptoms. J. Child Psychol. Psychiatry 52(2), 195–203 (2011)
Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273–297 (1995). https://doi.org/10.1007/BF00994018
Breiman, L.: Random forests. Mach. Learn. 45(5) (2001). https://doi.org/10.1023/a:1010933404324
Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation. In: Rumelhart, D.E., McClelland, J.L. (eds.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1. MIT Press (1986)
Marchand-Krynski, M-E., Morin-Moncet, O., Belanger, A-M., Beauchamp, M.H., Leonard, G.: Shared and differentiated motor skill impairments in children with dyslexia and/or attention deficit disorder: From simple to complex sequential coordination. PLoS ONE 12(5) (2017). https://doi.org/10.1371/journal.pone.0177490
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Davakumar, J., Siromoney, A. (2020). A Machine Learning Study of Comorbidity of Dyslexia and Attention Deficiency Hyperactivity Disorder. In: Chandrabose, A., Furbach, U., Ghosh, A., Kumar M., A. (eds) Computational Intelligence in Data Science. ICCIDS 2020. IFIP Advances in Information and Communication Technology, vol 578. Springer, Cham. https://doi.org/10.1007/978-3-030-63467-4_24
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DOI: https://doi.org/10.1007/978-3-030-63467-4_24
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