Deep learning with image-based autism spectrum disorder analysis: A systematic review

MZ Uddin, MA Shahriar, MN Mahamood… - … Applications of Artificial …, 2024 - Elsevier
Autism spectrum disorder (ASD) is a collection of neuro-developmental disorders associated
with social, communicational, and behavioral difficulties. Early detection thereof is necessary …

[HTML][HTML] Machine learning based on eye-tracking data to identify Autism Spectrum Disorder: A systematic review and meta-analysis

Q Wei, H Cao, Y Shi, X Xu, T Li - Journal of biomedical informatics, 2023 - Elsevier
Background Machine learning has been widely used to identify Autism Spectrum Disorder
(ASD) based on eye-tracking, but its accuracy is uncertain. We aimed to summarize the …

Hybrid techniques of facial feature image analysis for early detection of autism spectrum disorder based on combined CNN features

B Awaji, EM Senan, F Olayah, EA Alshari, M Alsulami… - Diagnostics, 2023 - mdpi.com
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized
by difficulties in social communication and repetitive behaviors. The exact causes of ASD …

Eye tracking biomarkers for autism spectrum disorder detection using machine learning and deep learning techniques

RA Jeyarani, R Senthilkumar - Research in Autism Spectrum Disorders, 2023 - Elsevier
Eye tracking is a promising tool for Autism Spectrum Disorder (ASD) detection in both
children and adults. An important aspect of social communication is keeping eye contact …

A face image classification method of autistic children based on the two-phase transfer learning

Y Li, WC Huang, PH Song - Frontiers in Psychology, 2023 - frontiersin.org
Autism spectrum disorder (ASD) is a neurodevelopmental disorder, which seriously affects
children's normal life. Screening potential autistic children before professional diagnose is …

Detection of ASD children through deep-learning application of fMRI

M Feng, J Xu - Children, 2023 - mdpi.com
Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable
immediate, targeted interventions. This study unveils an advanced convolutional-neural …

Diagnosis of autism spectrum disorder using convolutional neural networks

A Hendr, U Ozgunalp, M Erbilek Kaya - Electronics, 2023 - mdpi.com
Autism spectrum disorder as a condition has posed significant early diagnosis challenges to
the medical and health community for a long time. The early diagnosis of ASD is crucial for …

Autism screening at 18 months of age: a comparison of the Q-CHAT-10 and M-CHAT screeners

R Sturner, B Howard, P Bergmann, S Attar… - Molecular Autism, 2022 - Springer
Background Autism screening is recommended at 18-and 24-month pediatric well visits. The
Modified Checklist for Autism in Toddlers—Revised (M-CHAT-R) authors recommend a …

Applying eye tracking with deep learning techniques for early-stage detection of autism spectrum disorders

ZAT Ahmed, E Albalawi, THH Aldhyani, ME Jadhav… - Data, 2023 - mdpi.com
Autism spectrum disorder (ASD) poses a complex challenge to researchers and
practitioners, with its multifaceted etiology and varied manifestations. Timely intervention is …

Global trends and hotspots in the digital therapeutics of autism spectrum disorders: a bibliometric analysis from 2002 to 2022

X Wu, H Deng, S Jian, H Chen, Q Li, R Gong… - Frontiers in …, 2023 - frontiersin.org
Introduction Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that
has become a major cause of disability in children. Digital therapeutics (DTx) delivers …