The Detection of Autism Spectrum Disorder using Machine Learning

Authors

  • Gayatri D. Kolte Student, Department of Electronics and Telecommunication Engineering, Padm. V. B. Kolte College of Engineering, Malkapur, India
  • Y. P. Sushir Professor, Department of Electronics and Telecommunication Engineering, Padm. V. B. Kolte College of Engineering, Malkapur, India

Keywords:

Autism spectrum disorder, Machine Learning, Motor difficulties, Sensory problems

Abstract

Autism spectrum disorder (ASD) is a neuro-development disorder that affects a person’s interaction, communication and learning skills. These patients face different types of challenges such as difficulties with concentration, learning disabilities, mental health problems such as anxiety, depression, motor difficulties, sensory problems and many others. Autism spectrum disorder diagnosis can be done at any age but its symptoms generally appear in the first two years of life and develops through time. The main objective of this project is to predict the Autism Spectrum Disorder (ASD) at early stage (children between 12 to 36 months) using Machine Learning techniques. Also has capability to predict the ASD for age groups of 4-11 years, 12-17 years and for people of age 18 and more. The in depth analysis of ASD done by using latest techniques & technologies such as interactive framework (Smart Autism) [1] for screening and confirmation of autism, smart device (Autism Barta) based automated autism screening tool [2], Genetic Variant Analysis of Boys with Autism.

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Published

22-12-2021

Issue

Section

Articles

How to Cite

[1]
G. D. Kolte and Y. P. Sushir, “The Detection of Autism Spectrum Disorder using Machine Learning”, IJRESM, vol. 4, no. 12, pp. 77–78, Dec. 2021, Accessed: Dec. 14, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/1603