scholarly journals Prediction of ASD among Children using Machine Learning Techniques

2020 ◽  
Vol 9 (1) ◽  
pp. 1667-1670
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Machine Learning Techniques ◽  
Psychological Wellness ◽  
Learning Techniques ◽  
In The Beginning

Autism spectrum disorder (ASD) is a neurological issue that begins from early in childhood and proceeds all through such an individual's reality. It will influence that individual's conduct, speech with others, interference, and learning. Right now anyway, Autism Spectrum Disorder is to be distinguished in the beginning period, which is conceivable. Early acknowledgment of Autism Spectrum Disorder will improve the general psychological wellness of that particular youngster. The machine learning methodology is applied to diagnose Autism Spectrum Disorder (ASD), and in this work, we have used machine learning techniques and Optimization on an ASD dataset. We have employed XGBoost algorithms to the dataset considered, and as a result, efficient outputs are obtained. This will be incredible for the use of doctors to help them recognize Autism Spectrum Disorder at an early prior stage.

Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques

2020 ◽  
Vol 50 (11) ◽  
pp. 4039-4052 ◽  
Author(s):  
Kristine D. Cantin-Garside ◽  
Zhenyu Kong ◽  
Susan W. White ◽  
Ligia Antezana ◽  
Sunwook Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Machine Learning Techniques ◽  
Learning Techniques

Machine Learning Techniques for Analysing and Identifying Autism Spectrum Disorder

2021 ◽  
pp. 69-81
Author(s):  
Jyoti Bhola ◽  
Rubal Jeet ◽  
Malik Mustafa Mohammad Jawarneh ◽  
Shadab Adam Pattekari
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Prediction Models ◽  
Medical Diagnostics ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Machine Learning Techniques ◽  
Autistic Spectrum ◽  
Learning Techniques ◽  
Behavioural Condition

Autism spectrum disorder (ASD) is a neuro disorder in which a person's contact and connection with others has a lifetime impact. In all levels of development, autism can be diagnosed as a “behavioural condition,” since signs generally occur within the first two years of life. The ASD problem begins with puberty and goes on in adolescence and adulthood. In this chapter, an effort is being made to use the supporting vector machine (SVM) and the convolutionary neural network (CNN) for prediction and interpretation of children's ASD problems based on the increased use of machine learning methodology in the research dimension of medical diagnostics. On freely accessible autistic spectrum disorder screening dates in children's datasets, the suggested approaches are tested. Using different techniques of machine learning, the findings clearly conclude that CNN-based prediction models perform more precisely on the dataset for autistic spectrum disorders.

scholarly journals Optimization of Machine Learning Techniques on Autism Spectrum Disorder with Swarm Intelligence Based Feature Selection

2019 ◽  
Vol 8 (2) ◽  
pp. 6248-6251
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Feature Selection ◽  
Swarm Intelligence ◽  
Autism Spectrum ◽  
Machine Learning Algorithms ◽  
Spectrum Disorder ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Dsm V

This paper is a study on the various machine learning algorithms in order to perform ASD (Autism spectrum Disorder) as per the DSM-V standards. ASD occurs more frequently among children and in order to diagnose this with better accuracy, the study on binary firefly algorithm, a swarm intelligence based wrapper feature selection algorithm is used to obtain best results with optimum feature subsets. This paper will provide overall result after applying it to all types of machine learning models on supervised learning.

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