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Detecting Autism Spectrum Disorder using Machine Learning [article]

Md Delowar Hossain, Muhammad Ashad Kabir, Adnan Anwar, Md Zahidul Islam
2020 arXiv   pre-print
Autism Spectrum Disorder (ASD), which is a neuro development disorder, is often accompanied by sensory issues such an over sensitivity or under sensitivity to sounds and smells or touch.  ...  Our finding shows that Sequential minimal optimization (SMO) based Support Vector Machines (SVM) classifier outperforms all other benchmark machine learning algorithms in terms of accuracy during the detection  ...  Introduction Autism spectrum disorder (ASD), is a neurological developmental disorder. It affects how people communicate and interact with others, as well as how they behave and learn [1] .  ... 
arXiv:2009.14499v1 fatcat:ycy53ynw7zfj5ngis75e7ibryi

Detecting Autism Spectrum Disorders with Machine Learning Models Using Speech Transcripts [article]

Vikram Ramesh, Rida Assaf
2021 arXiv   pre-print
Autism spectrum disorder (ASD) can be defined as a neurodevelopmental disorder that affects how children interact, communicate and socialize with others.  ...  New technologies are rapidly emerging that include machine learning models using speech, computer vision from facial, retinal, and brain MRI images of patients to accurately and timely detect this disorder  ...  We used the CHILDES data bank and ASDBank English database for our research to predict autism spectrum disorder since the methods and analysis used are similar in both [20] , [21] .  ... 
arXiv:2110.03281v1 fatcat:oahmkwxu35fcnixatuljc247sm

Analysis and Detection of Autism Spectrum Disorder Using Machine Learning Techniques

Suman Raj, Sarfaraz Masood
2020 Procedia Computer Science  
Autism Spectrum Disorder (ASD) is a neuro-disorder in which a person has a lifelong effect on interaction and communication with others.  ...  Abstract Autism Spectrum Disorder (ASD) is a neuro-disorder in which a person has a lifelong effect on interaction and communication with others.  ...  Conclusion In this work, detection of Autism Spectrum Disorder was attempted using various machine learning and deep learning techniques.  ... 
doi:10.1016/j.procs.2020.03.399 fatcat:2dg2s6dxm5fslcbyw6tgljkafy

Explainable and Scalable Machine-Learning Algorithms for Detection of Autism Spectrum Disorder using fMRI Data [article]

Taban Eslami, Joseph S. Raiker, Fahad Saeed
2020 arXiv   pre-print
Diagnosing Autism Spectrum Disorder (ASD) is a challenging problem, and is based purely on behavioral descriptions of symptomology (DSM-5/ICD-10), and requires informants to observe children with disorder  ...  We have for the first time integrated traditional machine-learning and deep-learning techniques that allows us to isolate ASD biomarkers from MRI data sets.  ...  ASD-DiagNET: A hybrid learning technique for diagnosing Autism Spectrum Disorder using fMRI data Our recent model, called ASD-DiagNet [50] , proposes a two-stage dimensionality reduction process to reduce  ... 
arXiv:2003.01541v1 fatcat:p4hl7kioanhqbk4i6tumy7ba3u

Detecting Autism Spectrum Disorder Using Spectral Analysis of Electroretinogram and Machine Learning: Preliminary results Item

Sultan Mohammad Manjur, MD-Billal Hossain, Paul Constable, Dorothy Thompson, Fernando Marmolejo-Ramos, Hugo Posada-Quintero
INTRODUCTION Autism spectrum disorder (ASD) encompasses several neurodevelopmental disorders such as autistic disorder, childhood disintegrative disorder, etc. [1] .  ...  [16] proposed an artificial neural network (ANN) based approach using EEG signals to detect autism. Baygin et al.  ... 
doi:10.6084/m9.figshare.19633395.v1 fatcat:wr5d3f34mzbjdcsac56wjxqmmm

Eye Tracking-Based Diagnosis and Early Detection of Autism Spectrum Disorder Using Machine Learning and Deep Learning Techniques

Ibrahim Abdulrab Ahmed, Ebrahim Mohammed Senan, Taha H. Rassem, Mohammed A. H. Ali, Hamzeh Salameh Ahmad Shatnawi, Salwa Mutahar Alwazer, Mohammed Alshahrani
2022 Electronics  
Eye tracking is a useful technique for detecting autism spectrum disorder (ASD). One of the most important aspects of good learning is the ability to have atypical visual attention.  ...  In this study, three artificial-intelligence techniques were developed, namely, machine learning, deep learning, and a hybrid technique between them, for early diagnosis of autism.  ...  Yaneva et al. presented an approach to detecting autism in adults by eye-tracking. Eye movements were recorded, and machine learning algorithms were trained to detect autism.  ... 
doi:10.3390/electronics11040530 doaj:229435ab2e074ed5aec6cf702b985f03 fatcat:lkyf6atzebed7hcs6i5afxwe7u

Neural Network research adavances in 2020

José L. V. Sobrinho
2020 Zenodo  
Conclusively, raises questions about user's privacy and how tools like this can be used for better or for worse.  ...  Furthermore, discusses how soft computing methods such neural networks can be used to determine the popularity of a user's post.  ...  Autism Research and Treatment, 1-8. [2] Thabtah, F. (2018A) Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.  ... 
doi:10.5281/zenodo.3733980 fatcat:ujb4emoxfbbddoodj46kdsjyou


Rajani shree, Harshitha N, Prabha C S, Swathi N, Apoorva S
2020 International Research Journal of Computer Science  
Also, detecting autism traits through screening tests is expensive and time-consuming. The main aim is to propose an effective prediction model by adopting an advanced machine learning techniques.  ...  Autism Spectrum Disorder (ASD) is a neurodevelopment abnormality that affects the behavior and communication of an individual.  ...  So it can be used for decision making under ambiguity. Here in this paper they have applied machine learning techniques and validate their performance on a Autism Spectrum Disorder dataset.  ... 
doi:10.26562/irjcs.2020.v0705.006 fatcat:sl7w7wpisvg3phwdomwkgiahma

A Survey on Autism Spectrum Disorder (ASD) using Machine Learning

Suhas GK, Naveen N, Nagabanu M, Mario Edwin R, Nithish Kumar R
2021 Zenodo  
As the evolution of artificial intelligence and machine learning has created humongous impacts across various domains in our daily lives, it can be used to prognosticate autism with very little amount  ...  At present, Autism is a disorder procuring at a drastic rate without any proper set of measures in order to halt it.  ...  CONCLUSION & FUTURE SCOPE This paper talks about detection of autism spectrum disorder using machine learning.  ... 
doi:10.5281/zenodo.5340653 fatcat:24hhrxe3hbhqzmrjqz7rhihm4y

Machine Learning Advances in 2020

Mofleh Al Diabat
2020 Zenodo  
The HMM classification method attained the maximum accuracy in term of identification rate for informal with 80.1%, scientific phrases with 86%, and control with 63.8 % detection rates.  ...  For better word classification and recognition, discrete hidden markov model can be used and as they consider time distribution of speech signals.  ...  Classification of Autism Spectrum Disorder Using Random Support Vector Machine Cluster.  ... 
doi:10.5281/zenodo.3634371 fatcat:qcg6ysh73rf2jjbwxzmaoo37e4

Intervention of Autism Spectrum Disorder by ISAA Tool using Machine Learning

R. R. Naveen Kumar
2020 International Journal for Research in Applied Science and Engineering Technology  
Therefore the answer is converted into digitally and helps the doctor to predict the autism spectrum disorder using machine learning by applying various the classification methods. VIII.  ...  Autism spectrum disorder (ASD) is a brain and neural developmental disorder which cause difficulties with various communication, social and behavioral disorder.  ...  These paper that are to be discussed will help to identify screening process and how supervised machine learning algorithms are used to detect autism spectrum disorder. predicting ASD for people of any  ... 
doi:10.22214/ijraset.2020.6105 fatcat:icgylc3vnbazzbwhljwg4l7zla

Premature Identification of Autism Spectrum Disorder using Machine Learning Techniques

Suhas GK, Naveen N, Nagabanu M, Mario Edwin R, Nithish Kumar R
2021 Zenodo  
Autism Spectrum Disorder (ASD) is gaining traction quicker than ever before. Autism features can be detected by screening tests, but they are costly and time consuming.  ...  Autism can now be predicted within 12 to 36 months thanks to advances in artificial intelligence and machine learning (ML).  ...   This paper ["A Machine Learning Approach to Predict Autism Spectrum Disorder"] the work focused was On the development of the application for autism screening for autism spectrum disorder prediction  ... 
doi:10.5281/zenodo.5547026 fatcat:73xtypxcafc4plrdjebgqxzsue

Survey on Early Detection of Autism Using Data Mining Techniques

B Ida Seraphim, Lavi Samuel Rao, Shiwani Joshi
2018 International Journal of Engineering & Technology  
The children of today are the future of the nation and there are many hurdles in their development like ASD.ASD (Autism Spectrum Disorder) is a neurological disorder which has a lifetime impact on the  ...  The foremost goal of the paper is to know the number of people suffering from autism and the various symptoms of autism.  ...  Supervised learning is a type of machine learning algorithm which uses a known dataset.  ... 
doi:10.14419/ijet.v7i2.24.12003 fatcat:uzgafbwwh5ak7o5w2i6njujjty

Image Classification of Autism Spectrum Disorder Children Using Naïve Bayes Method With Hog Feature Extraction

Muhathir Muhathir, Rizki Muliono, Merri Hafni
Autism Spectrum Disorder (ASD) is a developmental disorder that affects a person's ability to communicate and interact socially.  ...  As a result, a system was developed in this study to detect Autism Spectrum Disorder in facial photos utilizing versions of the Nave Bayes approach and HoG feature extraction.  ...  K (2021) berjudul "Detection of Autism Spectrum Disorder in Children Using Machine Learning Techniques". Penelitian ini menggunakan metode machine learning.  ... 
doi:10.31289/jite.v5i2.6365 fatcat:xlmqtrdwcvfvbefvpvqsuxskxq

Exploration of Autism Spectrum Disorder using Classification Algorithms

B Deepa, K.S Jeen Marseline
2019 Procedia Computer Science  
Early stage of predicting autism disorder done with the help of using machine learning algorithms.  ...  Early stage of predicting autism disorder done with the help of using machine learning algorithms.  ...  There are several techniques available in data mining in which classification is one of the techniques used to assign items in a collection of target categories or classes [1] Autism spectrum disorder  ... 
doi:10.1016/j.procs.2020.01.098 fatcat:mwyspkn6undexo6b5yrhj7s3k4
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