ArticleBrain sciences2021
Deep Learning Approach for Screening Autism Spectrum Disorder in Children with Facial Images and Analysis of Ethnoracial Factors in Model Development and Application.
Article in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 83 citations in OpenAlex.
- AI-based recognition of facial and micro-expressions for the diagnosis of mental and neurological disorders: a systematic review.BMC psychiatry · 2025Pooled it
- Artificial intelligence, equity, and pediatric neurodevelopmental disorders: A scoping review of clinical practice applications.Pediatric investigation · 2026Review
- GeneticNAS: a novel self-evolving neural architecture for advanced ASD screening.Scientific reports · 2026Article
- Retraction Note: Deep learning approach to predict autism spectrum disorder: a systematic review and meta-analysis.BMC psychiatry · 2025Article
- A Scoping Review of AI-Based Approaches for Detecting Autism Traits Using Voice and Behavioral Data.Bioengineering (Basel, Switzerland) · 2025Review
- Deep Learning-Powered Down Syndrome Detection Using Facial Images.Life (Basel, Switzerland) · 2025Article
- The Role of Artificial Intelligence for Early Diagnostic Tools of Autism Spectrum Disorder: A Systematic Review.Turkish archives of pediatrics · 2025Article
- AI-assisted facial analysis in healthcare: From disease detection to comprehensive management.Patterns (New York, N.Y.) · 2025Review
- Innovative Strategies for Early Autism Diagnosis: Active Learning and Domain Adaptation Optimization.Diagnostics (Basel, Switzerland) · 2024Article
- Can micro-expressions be used as a biomarker for autism spectrum disorder?Frontiers in neuroinformatics · 2024Article
- Multi-Slice Generation sMRI and fMRI for Autism Spectrum Disorder Diagnosis Using 3D-CNN and Vision Transformers.Brain sciences · 2023Article
- Article
- Prediction Model for Sensory Perception Abnormality in Autism Spectrum Disorder.International journal of molecular sciences · 2023Article
- Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder.Frontiers in neuroinformatics · 2023Article
- A face image classification method of autistic children based on the two-phase transfer learning.Frontiers in psychology · 2023Article
- RETRACTED: Empirical Study of Autism Spectrum Disorder Diagnosis Using Facial Images by Improved Transfer Learning Approach.Bioengineering (Basel, Switzerland) · 2022Article
- Eye Tracking Research on the Influence of Spatial Frequency and Inversion Effect on Facial Expression Processing in Children with Autism Spectrum Disorder.Brain sciences · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autism spectrum disorder (ASD) is a developmental disability that can cause significant social, communication, and behavioral challenges. Early intervention for children with ASD can help to improve their intellectual ability and reduces autistic symptoms. Multiple clinical researches have suggested that facial phenotypic differences exist between ASD children and typically developing (TD) children. In this research, we propose a practical ASD screening solution using facial images through applying VGG16 transfer learning-based deep learning to a unique ASD dataset of clinically diagnosed children that we collected. Our model produced a 95% classification accuracy and 0.95 F1-score. The only other reported study using facial images to detect ASD was based on the Kaggle ASD Facial Image Dataset, which is an internet search-produced, low-quality, and low-fidelity dataset. Our results support the clinical findings of facial feature differences between children with ASD and TD children. The high F1-score achieved indicates that it is viable to use deep learning models to screen children with ASD. We concluded that the racial and ethnic-related factors in deep-learning based ASD screening with facial images are critical to solution viability and accuracy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.