Open AccessIntelligent Frame Work to Predict Autism in Infants using Machine Learning
Author(s) -
S. V. Evangelin Sonia,
Ravi Prasanth,
B. Mythreyei,
A. Harshavardhan,
Arya Manoharan
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.a1997.059120
Subject(s) - autism spectrum disorder , autism , neurodevelopmental disorder , reliability (semiconductor) , psychology , frame (networking) , frame work , artificial intelligence , cognition , machine learning , computer science , audiology , developmental psychology , cognitive psychology , psychiatry , medicine , engineering , architectural engineering , telecommunications , power (physics) , physics , quantum mechanics
Autistic Spectrum Disorder (ASD) is a behavioral impairment that interferes with the use of auditory, communicative, cognitive, abilities and social skills. ADS was introduce researched using advanced approaches based on machine learning to speed up the diagnostic period or increase the responsiveness, reliability or precision of the diagnosis process. Normal medical checkup data (training data) of the baby, test data is used to classify the child with autism. The assessment results showed that, for both types of datasets, the proposed prediction model produces better results in terms of precision, responsiveness, precision and false positive rate (FPR). In the modern day, Autism Spectrum Disorder (ASD) is gaining some momentum quicker than ever. Detecting signs of autism by screening tests is very costly and time consuming. Autism can be identified faster by combining artificial intelligence and Machine Learning (ML).