Identifying children with autism spectrum disorder based on their face processing abnormality: a machine learning framework

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Items 101–200 of 297

1. Neural correlates of facial recognition deficits in autism spectrum disorder: a comprehensive review
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2. Summarizing Recent Developments on Autism Spectrum Disorder Detection and Classification Through Machine Learning and Deep Learning Techniques
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3. EyeXplain Autism: Interactive System for Eye Tracking Data Analysis and Deep Neural Network Interpretation for Autism Spectrum Disorder Diagnosis
   Ryan Anthony J. de Belen, Tomasz Piotr Bednarz, Arcot Sowmya · 2021 · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA)
4. Artificial intelligence and pediatrics: A synthetic mini review
   Peter Kokol, Jernej Završnik, Helena Blažun Vošner · 2017 · Pediatric Dimensions
5. Gaze-based classification of autism spectrum disorder
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6. An intelligent multimodal framework for identifying children with autism spectrum disorder
   Jingying Chen, Mengyi Liao, Guangshuai Wang, Chang Chen · 2020 · International Journal of Applied Mathematics and Computer Science
7. Attention Level Evaluation in Children With Autism: Leveraging Head Pose and Gaze Parameters From Videos for Educational Intervention
   Elizabeth B. Varghese, Marwa Qaraqe, Dena Al‐Thani · 2024 · IEEE Transactions on Learning Technologies
8. Digitally assisted diagnostics of autism spectrum disorder
   Jana Christina Koehler, Christine M. Falter‐Wagner · 2023 · Frontiers in Psychiatry
9. Classifying autism in a clinical population based on motion synchrony: a proof-of-concept study using real-life diagnostic interviews
   Jana Christina Koehler, Mark Sen Dong, Da‐Yea Song, Guiyoung Bong, Nikolaos Koutsouleris, Hee‐Jeong Yoo, Christine M. Falter‐Wagner · 2024 · Scientific Reports
10. Intelligent Gaze-Based Screening System for Autism
    Alanoud Bin Dris, AbdulMalik S. Al‐Salman, Areej Al‐Wabil, Mohammed Aldosari · 2019 · International Conference on Computer Applications & Information Security (ICCAIS)
11. Face-based machine learning diagnostics: applications, challenges and opportunities
    Jie Song, Mengqiao He, Xin Zheng, Yuxin Zhang, Cheng Bi, Jinhua Feng, Jiahui Du, Hang Li, Bairong Shen · 2025 · Artificial Intelligence Review
12. Classifying Eye-Tracking Data Using Saliency Maps
    Shafin Rahman, Sejuti Rahman, Omar Shahid, Md. Tahmeed Abdullah, Jubair Ahmed Sourov · 2021 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
13. Exploring tree-based machine learning methods to predict autism spectrum disorder
    Kazi Shahrukh Omar, Muhammad Nazrul Islam, Nabila Shahnaz Khan · 2021 · Elsevier eBooks
14. Automated ASD detection in children from raw speech using customized STFT-CNN model
    Kurma Venkata Keerthana Sai, Rompicharla Thanmayee Krishna, Kodali Radha, Dhulipalla Venkata Rao, Abdul Muneera · 2024 · International Journal of Speech Technology
15. Uncertainty Inspired Early Autism Spectrum Disorder Screening via Contrastive Image-Viewing Paradigm
    Ying Zhang, Yaping Huang, Jiansong Qi, Sihui Zhang, Mei Tian, Yi Tian, Fanchao Meng, Lin Guan, Ting-Hsun Chang · 2024 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
16. Modeling Therapeutic Alliance in the Age of Telepsychiatry
    Jihan Ryu, David Banthin, Xiaosi Gu · 2020 · Trends in Cognitive Sciences
17. Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework
    Jin Xie, Longfei Wang, Paula J. Webster, Yao Yang, Jiayao Sun, Shuo Wang, Huihui Zhou · 2022 · Interdisciplinary Sciences Computational Life Sciences
18. Identifying autism spectrum disorder symptoms using response and gaze behavior during the Go/NoGo game CatChicken
    Prasetia Utama Putra, Keisuke Shima, Sergio A. Álvarez, Koji Shimatani · 2021 · Scientific Reports
19. Gaze-based Screening of Autistic Traits for Adolescents and Young Adults using Prosaic Videos
    Karan Ahuja, Abhishek Bose, Mohit Jain, Kuntal Dey, Anil Joshi, Krishnaveni Achary, Blessin Varkey, Chris Harrison, Mayank Goel · 2020 · ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS)
20. Diagnosing autism spectrum disorder based on eye tracking technology using deep learning models
    Mosleh Hmoud Al-Adhaileh, Saleh Nagi Alsubari, Abdullah Hamoud Abdulrahman Al-Nefaie, Sultan Ahmad, Ayoub K. Al-Hamadi · 2025 · Frontiers in Medicine
21. Effects of data preprocessing on detecting autism in adults using web-based eye-tracking data
    Erfan Khalaji, Sukru Eraslan, Yeliz Yeşilada, Victoria Yaneva · 2022 · Behaviour and Information Technology
22. Recommendation Learning System Model for Children with Autism
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23. Machine learning-based diagnosis of autism spectrum disorder in children and adolescents using eye-tracking data: a systematic review and meta-analysis
    Wenhao Han, Xinyu Yang, Xin Li, Jiacheng Wang, Juan Liu, Wei Pang · 2025 · International Journal of Medical Informatics
24. Machine learning in automated diagnosis of autism spectrum disorder: a comprehensive review
    Khosro Rezaee · 2025 · Computer Science Review · Retracted
25. Predicting Employer Recruitment of Individuals with Autism Spectrum Disorders with Decision Trees
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26. Identify autism spectrum disorder via dynamic filter and deep spatiotemporal feature extraction
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27. A Novel Eye Movement Data Transformation Technique that Preserves Temporal Information: A Demonstration in a Face Processing Task
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28. Automated Autism Detection Based on Characterizing Observable Patterns From Photos
    Alice Z. Guo · 2020 · IEEE Transactions on Affective Computing
29. Use of Oculomotor Behavior to Classify Children with Autism and Typical Development: A Novel Implementation of the Machine Learning Approach
    Zhong Zhao, Jiwei Wei, Jiayi Xing, Xiaobin Zhang, Xingda Qu, Xinyao Hu, Jianping Lu · 2022 · Journal of Autism and Developmental Disorders
30. Using visual attention estimation on videos for automated prediction of autism spectrum disorder and symptom severity in preschool children
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31. Suppressing Uncertainty in Gaze Estimation
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32. Early detection of ASD Traits in Children using CNN
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33. Identification of Autism Spectrum Disorder via an Eye-Tracking Based Representation Learning Model
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34. A new bio-inspired metric based on eye movement data for classifying ASD and typically developing children
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35. Diagnosing Autism Spectrum Disorder Using Machine Learning Techniques
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36. Can smartphones be used for routine dental clinical application? A validation study for using smartphone-generated 3D facial images
    Pradeep Singh, Tai-Chiu Hsung, Deepal Haresh Ajmera, Yiu Yan Leung, Colman P. J. McGrath, Min Gu · 2023 · Journal of Dentistry
37. Comparison of Classification Algorithms of the Autism Spectrum Disorder Diagnosis
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38. Verbal fluency as a predictor of autism spectrum disorder diagnosis and co-occurring attention-deficit/hyperactivity disorder symptoms
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39. Novel analysis of fNIRS acquired dynamic hemoglobin concentrations: application in young children with autism spectrum disorder
    Yanwei Li, Huibin Jia, Dongchuan Yu · 2018 · Biomedical Optics Express
40. A Convolutional Neural Network for gaze preference detection: A potential tool for diagnostics of autism spectrum disorder in children
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41. Deep Learning to Interpret Autism Spectrum Disorder Behind the Camera
    Shi Chen, Ming Xin Jiang, Qi Zhao · 2024 · IEEE Transactions on Cognitive and Developmental Systems
42. RETRACTED ARTICLE: A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection
    Rodrigo Colnago Contreras, Monique Simplicio Viana, Victor José Souza Bernardino, Francisco Lledo dos Santos, Önsen Toygar, Rodrigo Capobianco Guido · 2025 · Scientific Reports · Retracted
43. The role of machine learning in autism spectrum disorder assessment and management
    Aoife Reilly, Nicola Walsh, Daniel P. O’Reilly, Miriam Smyth, Kathleen Mary Gorman, Sarah Ostadabbas, Claire Power · 2025 · Pediatric Research
44. Predictive Analysis of Autism Spectrum Disorder (ASD) using Machine Learning
    Naurin Farooqi, Faisal Bukhari, Waheed Iqbal · 2021 · International Conference on Frontiers of Information Technology (FIT)
45. MeltdownCrisis: Dataset of Autistic Children During Meltdown Crisis
    Marwa Masmoudi, Salma Kammoun Jarraya, Mohamed Hammami · 2019 · International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
46. Autism Spectrum Disorder diagnosis based on trajectories of eye tracking data
    Thiago V. Cardoso, Gabriel C. Michelassi, Felipe O. Franco, Fernando Mitsuo Sumiya, Joana Portolese, Helena Brentani, Ariane Machado‐Lima, Fátima L. S. Nunes · 2021 · Proceedings - IEEE Symposium on Computer-Based Medical Systems
47. Detecting Children with Autism Spectrum Disorder Based on Eye-tracking and Machine Learning
    Hsin-Yi Lu, Yang‐Cheng Lin, Chia‐Hsin Chen, Chih-Chung Wang, Ia-Wen Han, Wen-Lung Liang · 2023 · IEEE International Conference on Knowledge Innovation and Invention (ICKII)
48. Effectiveness of Mental Health Care by Using Machine Learning on Manufacturing Worker
    Jongwoo Lim, Suhan Lee, Jinhong Noh, Wonhee Lee, Pei‐Chen Su, Yong‐Jin Yoon · 2023 · International Journal of Precision Engineering and Manufacturing-Smart Technology
49. Enhancing ensemble classifiers utilizing gaze tracking data for autism spectrum disorder diagnosis
    Rafaela Oliveira da Silva Sá, Gabriel C. Michelassi, Diego Dos Santos Butrico, Felipe O. Franco, Fernando Mitsuo Sumiya, Joana Portolese, Helena Brentani, Fátima L. S. Nunes, Ariane Machado‐Lima · 2024 · Computers in Biology and Medicine
50. Multi-modal data analysis for autism spectrum disorder in children: State of the art and trends
    Lukai Pang, Xiaoke Zhao, Lulu Zhao, Jianqing Li, Fengyi Kuo, Hongxing Wang, Chengyu Liu · 2025 · EngMedicine
51. RETRACTED CHAPTER: Facial Feature Analysis for Autism Detection Using Deep Learning
    Anjali Singh, Mitali Laroia, Abha Rawat, K. R. Seeja · 2023 · Lecture notes in networks and systems
52. Computing Multimodal Dyadic Behaviors During Spontaneous Diagnosis Interviews Toward Automatic Categorization of Autism Spectrum Disorder
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53. Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier
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54. Responsive Social Smile: A Machine Learning based Multimodal Behavior Assessment Framework towards Early Stage Autism Screening
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55. Dynamic eye avoidance patterns in the high autistic traits group: An eye-tracking study
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56. Machine learning based autism screening tool—a modified approach
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57. Classification of Autism Spectrum Disorder using CNN & Transfer Learning
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58. Autism Spectrum Disorder Prediction Using Machine Learning and Design Science
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59. Autism Spectrum Disorder Diagnosis Using Ensemble ML and Max Voting Techniques
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60. Trends and features of autism spectrum disorder research using artificial intelligence techniques: a bibliometric approach
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61. Early-stage autism diagnosis using action videos and contrastive feature learning
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62. Analysis of Autistic Spectrum Disorder Screening Data for Adolescents
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63. Physics Augmented Tuple Transformer for Autism Severity-Level Detection
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64. Atypical audio-visual neural synchrony and speech processing in early autism
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65. Design, Development, and a Pilot Study of a Low-Cost Robot for Child–Robot Interaction in Autism Interventions
    Ilias A. Katsanis, Vassilis C. Moulianitis, Diamantis T. Panagiotarakos · 2022 · Multimodal Technologies and Interaction
66. Interpersonal Motor Coordination in Children with Autism and the Establishment of Machine Learning Models to Objectively Classify Children with Autism and Typical Development
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67. Risk assessment and automatic identification of autistic children based on appearance
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68. Data-Driven Characterization of Individuals With Delayed Autism Diagnosis
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69. ML-PASD
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70. Social Skills in Autism Spectrum Disorders
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71. Autism screening for children based on appearance features across multiple paradigms
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72. Activity-based Early Autism Diagnosis Using A Multi-Dataset Supervised Contrastive Learning Approach
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73. A review of machine learning-based methods for automatically detecting autism spectrum disorder in children's faces
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74. A Learning Paradigm for Selecting Few Discriminative Stimuli in Eye-Tracking Research
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75. [Retracted] Early Detection of Autism Spectrum Disorders (ASD) with the Help of Data Mining Tools
    Ammar Akram Abdulrazzaq, Sana Sulaiman Hamid, Asaad T. Al‐Douri, Abdulsattar Abdullah Hamad Mohamad, Abdelrahman Mohamed Ibrahim · 2022 · BioMed Research International · Retracted
76. Early diagnosis of Autism using Machine Learning techniques and Gated Recurrent Units
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77. A Hybrid Approach to Support the Detection of Autism Spectrum Disorder(ASD) through Machine Learning and Deep Learning Techniques
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78. Learning Lexical Coherence Representation Using LSTM Forget Gate for Children with Autism Spectrum Disorder During Story-Telling
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79. A Survey on the Application of the Internet of Things in the Diagnosis of Autism Spectrum Disorder
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80. Early Detection of Autism Spectrum Disorder (ASD) Using Machine Learning Techniques: A Review
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81. Big data approaches to develop a comprehensive and accurate tool aimed at improving autism spectrum disorder diagnosis and subtype stratification
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82. An image-based analytics framework for early autism detection using eye movements
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84. ML Algorithms that have been Utilised to Classify Neuro-Developmental Disorders: A Review
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85. Enhancing Autism Severity Classification: Integrating LSTM into CNNs for Multisite Meltdown Grading
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86. Comparative Exploration of Machine Learning Models for Enhanced Autism Detection
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87. Machine Learning-Based Detection and Classification of Neurodevelopmental Disorders from Speech Patterns
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88. Deep Learning Methods on Recognizing Autism Spectrum Disorder
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90. Early Autism Screening in Children Using Facial Recognition
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91. ASSOCIATION RULES BASED CLASSIFICATION FOR AUTISM SPECTRUM DISORDER DETECTION
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92. Accurate Estimate of Autism Spectrum Disorder in Children Utilizing Several Machine Learning Techniques
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94. Autism Disease Prediction Using Deep Learning & Transfer Learning
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95. Analyzing Behavioral Markers of Autistic Children Using Eye Tracking Data
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97. Uncertainty Inspired Autism Spectrum Disorder Screening
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98. A Review of Machine Learning Models for Predicting Autism Spectrum Disorder
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99. Recognition of autism spectrum disorder based on face processing abnormality
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100. Machine Learning based novel Autism Spectrum Disorder Screening
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