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Survey on Behavioural Analysis of ASD using Clustering Techniques
As database and networking technologies are increasing rapidly, as web medical information is available to collect data and store which in turn can be used for more than a few medical practices data mining strategies are used in healthcare device to become aware of the various behaviors of autistic teens. This paper discusses the importance of clustering strategies like k capacity and dB scan to find out about the behaviours of asd young people.
Keywords
Clustering, Autism Spectrum Disorders, K-Means, DBSCAN.
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- E. Lane, R. L. Young, A. E. Baker, and M. T. Angley. Sensory processing subtypes in autism: affiliation with adaptive behaviour. Journal of autism and developmental disorders, 40(1):112–122, 2010. [9] E.
- Linstead, D. Dixon, E. Hong, C. Burns, R. French, M. Novack, and D. Granpeesheh. A comparison of the results of depth and length on results throughout therapy domains for children with autism spectrum disorder. Translational Psychiatry, 7(9), 2017. [10] E. Linstead, D. R. Dixon, R. French, D. Granpeesheh,
- H. Adams, R. German, A. Powell, E. Stevens, J. Tarbox, and J. Karnack. Intensity and learning outcomes in the treatment of children with autism spectrum disorder. Behaviour Modification, 2016. [11] E. Linstead,
- R. German, D. Dixon, D. Granpeesheh, M. Novak, and A Powell and utility of neural networks to predicting mastery of learning results in the treatment of autism spectrum disease. In Machine Learning and Applications, 2015. ICMLA ’15, pages 414– 418. IEEE, 2015.
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