Recommended System For Wellness Of Autistic Children Using Data Analytics and Machine Learning

• Published in: IOP conference series. Materials Science and Engineering Vol. 1055; no. 1; pp. 12101 - 12107
• Main Authors: Karre, Kusumalatha, Rama Devi, Y
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.02.2021
• Subjects: Algorithms; Autism; Communication skills; Developmental Screening Test (DST); Diet; Early intervention; Functional Assessment Checklist for Programming (facp); Machine learning
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/1055/1/012101

Autism is a mental condition which hinders social and communication skills. It's a lifelong disability which makes the child's day to day life very difficult. But in most of the cases early intervention has helped the children to develop the skills which are needed to the fullest to overcome autism. As early the intervention, better the development of the child. Most of the research has been carried out to detect the autism using various machine learning algorithms which consider autistic diagnostic tools such as ADI-R, ADOS or CARS. Once autism is detected, different areas which need to be developed are considered and recommendations are given to the child. In this paper, a system is proposed which uses multi dimensional data collected from facp, DST and Diet to perform analytics using machine learning and provide recommendations to the child.