A Significant Improvement Approach Towards the Detection of Autism Spectrum Disorder using Data Sciences

A complex disorder called ASD (Autism Spectrum Disorder) is characterised by persistent problems with social communication, narrow interests, and repetitive behaviour. ASD sufferers may behave, communicate, interact, and learn in different ways from the average person. The majority of the time, their appearance does not set them apart from others. ASD sufferers may be highly talented in many different areas. For instance, some people with ASD may be highly communicative while others are nonverbal. While some people with ASD need significant daily support, others are able to live and work independently. Parents and caretakers can find early signs of this condition before a child becomes one year old. However, by the time the child is two or three years old, the symptoms are typically more severe. Here artificial intelligence techniques and data science techniques can be used. This paper presents a novel approach for detecting ASD from relevant observations in the patients. Differences in results between the two types of neural networks used have been shown as well.