Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29328, first published .
Classification of Children With Autism and Typical Development Using Eye-Tracking Data From Face-to-Face Conversations: Machine Learning Model Development and Performance Evaluation

Classification of Children With Autism and Typical Development Using Eye-Tracking Data From Face-to-Face Conversations: Machine Learning Model Development and Performance Evaluation

Classification of Children With Autism and Typical Development Using Eye-Tracking Data From Face-to-Face Conversations: Machine Learning Model Development and Performance Evaluation

Journals

  1. (previously Marzena Szkodo) M, Micai M, Caruso A, Fulceri F, Fazio M, Scattoni M. Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review. Neuroscience & Biobehavioral Reviews 2023;145:105021 View
  2. Wei Q, Cao H, Shi Y, Xu X, Li T. Machine learning based on eye-tracking data to identify Autism Spectrum Disorder: A systematic review and meta-analysis. Journal of Biomedical Informatics 2023;137:104254 View
  3. Putra P, Shima K, Alvarez S, Shimatani K. Identifying autism spectrum disorder symptoms using response and gaze behavior during the Go/NoGo game CatChicken. Scientific Reports 2021;11(1) View
  4. Alcañiz M, Chicchi‐Giglioli I, Carrasco‐Ribelles L, Marín‐Morales J, Minissi M, Teruel‐García G, Sirera M, Abad L. Eye gaze as a biomarker in the recognition of autism spectrum disorder using virtual reality and machine learning: A proof of concept for diagnosis. Autism Research 2022;15(1):131 View
  5. Zhao Z, Wei J, Xing J, Zhang X, Qu X, Hu X, Lu J. Use of Oculomotor Behavior to Classify Children with Autism and Typical Development: A Novel Implementation of the Machine Learning Approach. Journal of Autism and Developmental Disorders 2023;53(3):934 View
  6. Kollias K, Syriopoulou-Delli C, Sarigiannidis P, Fragulis G. The Contribution of Machine Learning and Eye-Tracking Technology in Autism Spectrum Disorder Research: A Systematic Review. Electronics 2021;10(23):2982 View
  7. Ma Z, Xu L, Li Q, Li X, Shi Y, Zhang X, Yang Y, Wang J, Fan L, Wu L. Prediction Model for Sensory Perception Abnormality in Autism Spectrum Disorder. International Journal of Molecular Sciences 2023;24(3):2367 View
  8. Ahmed I, Senan E, Rassem T, Ali M, Shatnawi H, Alwazer S, Alshahrani M. Eye Tracking-Based Diagnosis and Early Detection of Autism Spectrum Disorder Using Machine Learning and Deep Learning Techniques. Electronics 2022;11(4):530 View
  9. Milano N, Simeoli R, Rega A, Marocco D. A deep learning latent variable model to identify children with autism through motor abnormalities. Frontiers in Psychology 2023;14 View
  10. Asmetha Jeyarani R, Senthilkumar R. Eye Tracking Biomarkers for Autism Spectrum Disorder Detection using Machine Learning and Deep Learning Techniques: Review. Research in Autism Spectrum Disorders 2023;108:102228 View
  11. Awaji B, Senan E, Olayah F, Alshari E, Alsulami M, Abosaq H, Alqahtani J, Janrao P. Hybrid Techniques of Facial Feature Image Analysis for Early Detection of Autism Spectrum Disorder Based on Combined CNN Features. Diagnostics 2023;13(18):2948 View
  12. Zheng Y, Liu C, Lai N, Wang Q, Xia Q, Sun X, Zhang S. Current development of biosensing technologies towards diagnosis of mental diseases. Frontiers in Bioengineering and Biotechnology 2023;11 View
  13. Lestarevic S, Kalanj M, Milutinovic L, Grujicic R, Vasic J, Maslak J, Mitkovic-Voncina M, Ljubomirovic N, Pejovic-Milovancevic M. Internal Consistency of the Serbian Translation of the Stanford Social Dimensions Scale and Association to Strengths and Difficulties Questionnaire Scores in Male and Female Individuals on the Autism Spectrum and Non-autistic Individuals. Journal of Autism and Developmental Disorders 2024;54(9):3423 View
  14. Cheng M, Zhang Y, Xie Y, Pan Y, Li X, Liu W, Yu C, Zhang D, Xing Y, Huang X, Wang F, You C, Zou Y, Liu Y, Liang F, Zhu H, Tang C, Deng H, Zou X, Li M. Computer-Aided Autism Spectrum Disorder Diagnosis With Behavior Signal Processing. IEEE Transactions on Affective Computing 2023;14(4):2982 View
  15. Sha M, Alqahtani A, Alsubai S, Dutta A. Modified Meta Heuristic BAT with ML Classifiers for Detection of Autism Spectrum Disorder. Biomolecules 2023;14(1):48 View
  16. Ziv I, Avni I, Dinstein I, Meiri G, Bonneh Y. Oculomotor randomness is higher in autistic children and increases with the severity of symptoms. Autism Research 2024;17(2):249 View
  17. de Belen R, Eapen V, Bednarz T, Sowmya A, Coutrot A. Using visual attention estimation on videos for automated prediction of autism spectrum disorder and symptom severity in preschool children. PLOS ONE 2024;19(2):e0282818 View
  18. Simeoli R, Rega A, Cerasuolo M, Nappo R, Marocco D. Using Machine Learning for Motion Analysis to Early Detect Autism Spectrum Disorder: A Systematic Review. Review Journal of Autism and Developmental Disorders 2024 View
  19. Zhou W, Yang M, Tang J, Wang J, Hu B. Gaze Patterns in Children With Autism Spectrum Disorder to Emotional Faces: Scanpath and Similarity. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2024;32:865 View
  20. Mohd Salah Aljabiri S, Hamdan M. Analyzing lower body movements using machine learning to classify autistic children. Biomedical Signal Processing and Control 2024;94:106288 View
  21. Wei Q, Dong W, Yu D, Wang K, Yang T, Xiao Y, Long D, Xiong H, Chen J, Xu X, Li T. Early identification of autism spectrum disorder based on machine learning with eye-tracking data. Journal of Affective Disorders 2024;358:326 View
  22. Jia Q, Wang X, Li X, Xie C, Zhang Q, Mu J, Yang W. Analysis of research hotspots and trends in pediatric ophthalmopathy based on 10 years of WoSCC literature. Frontiers in Pediatrics 2024;12 View
  23. Zhao Z, Zhang X, Zhang X, Qu X, Hu X, Lu J. Interpersonal Motor Coordination in Children with Autism and the Establishment of Machine Learning Models to Objectively Classify Children with Autism and Typical Development. IRBM 2024;45(5):100838 View
  24. Jia S, Jing J, Yang C. A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods. Journal of Autism and Developmental Disorders 2025;55(9):3011 View
  25. Nie W, Zhou B, Wang Z, Chen B, Wang X, Hu C, Li H, Xu Q, Xu X, Liu H. Computational Interpersonal Communication Model for Screening Autistic Toddlers: A Case Study of Response-to-Name. IEEE Journal of Biomedical and Health Informatics 2024;28(6):3683 View
  26. Liu Z, Yeh W, Lin K, Lin C, Chang C. Machine learning based approach for exploring online shopping behavior and preferences with eye tracking. Computer Science and Information Systems 2024;21(2):593 View
  27. Cerasuolo M, De Marco S, Nappo R, Simeoli R, Rega A. The Potential of Virtual Reality to Improve Diagnostic Assessment by Boosting Autism Spectrum Disorder Traits: A Systematic Review. Advances in Neurodevelopmental Disorders 2025;9(1):1 View
  28. Liu Z, Li J, Zhang Y, Wu D, Huo Y, Yang J, Zhang M, Dong C, Jiang L, Sun R, Zhou R, Li F, Yu X, Zhu D, Guo Y, Chen J. Auxiliary Diagnosis of Children With Attention-Deficit/Hyperactivity Disorder Using Eye-Tracking and Digital Biomarkers: Case-Control Study. JMIR mHealth and uHealth 2024;12:e58927 View
  29. Eraslan S, Yesilada Y, Shafique A, Yaneva V, Ha L. A systematic evaluation of autism spectrum disorder identification with Scanpath Trend Analysis (STA). Biomedical Signal Processing and Control 2025;103:107414 View
  30. Jaradat A, Wedyan M, Alomari S, Barhoush M. Using Machine Learning to Diagnose Autism Based on Eye Tracking Technology. Diagnostics 2024;15(1):66 View
  31. Ranjana J, Muthukkumar R. ADET MODEL: Real time autism detection via eye tracking model using retinal scan images. Technology and Health Care 2025;33(4):1661 View
  32. Ziyad S, Aljohani E, Saeed I. Diagnosis of Autism Spectrum Disorder by Imperialistic Competitive Algorithm and Logistic Regression Classifier. Computers, Materials & Continua 2023;77(2):1515 View
  33. Setu D. A Systematic Review of Developments in Eye Tracking and Machine Learning for the Early Detection of Autism Spectrum Disorder. Journal of Technology in Behavioral Science 2025 View
  34. Nguyen T, Nguyen T, Le T, Ngo T. Eye-tracking technology applications for supporting individuals with autism spectrum disorder: insights, challenges, and opportunities. Disability and Rehabilitation: Assistive Technology 2025;20(8):2630 View
  35. Sun C, McEwan A, Boulton K, Demetriou E, Sadozai A, Lampit A, Guastella A. Artificial intelligence for tracking social behaviours and supporting an autism spectrum disorder diagnosis: systematic review and meta-analysis. eBioMedicine 2025;120:105931 View
  36. Al-Adhaileh M, Alsubari S, Al-Nefaie A, Ahmad S, Alhamadi A. Diagnosing autism spectrum disorder based on eye tracking technology using deep learning models. Frontiers in Medicine 2025;12 View
  37. Zhao Z, Qiu Z, Zhang X, Qu X, Hu X, Lu J. Social Whole-Body Movement Aids the Objective Classification of Children With Autism and Typical Development by Implementing a Machine Learning Approach. IEEE Transactions on Human-Machine Systems 2025;55(5):707 View
  38. Coelho F, Rando B, Salgado M, Abreu A. Sensory Processing of Time and Space in Autistic Children. Children 2025;12(10):1366 View
  39. Rakotomanana H, Rouhafzay G. A Scoping Review of AI-Based Approaches for Detecting Autism Traits Using Voice and Behavioral Data. Bioengineering 2025;12(11):1136 View
  40. Habib G, Malik I, Sharma S, Singh S, Kim J. Optimizing MobileNetV3 for multimodal eye gaze and emotion recognition via advanced pruning and quantisation techniques. Scientific Reports 2025;15(1) View
  41. Shilpa R, Vinay B, Rajendra A. A review of emerging non-invasive techniques for early autism spectrum disorder detection: insights from AI and biomarkers. International Journal of Developmental Disabilities 2025:1 View
  42. Reilly A, Walsh N, O’Reilly D, Smyth M, Gorman K, Ostadabbas S, Power C. The role of machine learning in autism spectrum disorder assessment and management. Pediatric Research 2025 View

Books/Policy Documents

  1. Rabbi M, Zohra F, Hossain F, Akhi N, Khan S, Mahbub K, Biswas M. Recent Trends in Image Processing and Pattern Recognition. View
  2. Magboo V, Magboo M. Artificial Intelligence and Data Science. View
  3. Singh A, Laroia M, Rawat A, Seeja K. International Conference on Innovative Computing and Communications. View
  4. Mitra S, Srinath K, Gowri Manohari V, Poornima D, Karunya K. ICT Analysis and Applications. View
  5. Lee S, Mun J, Kim S, Park H, Yang S, Kim H, Noh S, Kim W, Chung M. Computers Helping People with Special Needs. View
  6. Varghese E, Qaraqe M, Al-Thani D. The Impact of Artificial Intelligence on Societies. View
  7. Deepa V, Maheswari D. Artificial Intelligence Based Smart and Secured Applications. View
  8. Smrity A, Rahman S, Joy M, Shamim Kaiser M. Applied Intelligence and Informatics. View

Conference Proceedings

  1. Shamseddine H, Otoum S, Mourad A. GLOBECOM 2022 - 2022 IEEE Global Communications Conference. On the Feasibility of Federated Learning for Neurodevelopmental Disorders: ASD Detection Use-Case View
  2. Kavitha V, Siva R. 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS). Review of Machine Learning Algorithms for Autism Spectrum Disorder Prediction View
  3. Bidwe R, Mishra S, Bajaj S. Proceedings of the 2023 Fifteenth International Conference on Contemporary Computing. Performance evaluation of Transfer Learning models for ASD prediction using non-clinical analysis View
  4. Zhang A. 2023 IEEE 3rd International Conference on Data Science and Computer Application (ICDSCA). A Novel Eye-tracking and Audio Hybrid System for Autism Spectrum Disorder Early Detection View
  5. R S, G B. 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). Deep Learning for Autism Detection Using Eye Tracking Scanpaths View
  6. Liu L, Chen G, Liu L, Li S, Ling Y. 2024 5th International Conference on Computer Engineering and Application (ICCEA). A method for Early Autism Spectrum Disorder Screening based on Gaze Tasks View
  7. Cheekaty S, Muneeswari G. SMART GRID & ELECTRIC VEHICLE. Early detection of autism spectrum disorder in children: A review View
  8. Kollias K, Maraslidis G, Sarigiannidis P, Fragulis G. ETLTC2024 INTERNATIONAL CONFERENCE SERIES ON ICT, ENTERTAINMENT TECHNOLOGIES, AND INTELLIGENT INFORMATION MANAGEMENT IN EDUCATION AND INDUSTRY. Application of machine learning on eye-tracking data for autism detection: The case of high-functioning adults View
  9. Karpagam C, Deepa C. 2024 5th International Conference on Smart Electronics and Communication (ICOSEC). Detection of Autism Spectrum Disorder in Eye Tracking using Hybrid Machine Learning and Deep Learning Technique View
  10. Das D, Shit S. 2024 4th International Conference on Artificial Intelligence and Signal Processing (AISP). Early Detection of Mental Health Using Eye Movement Data: A Cost-Effective Approach on Real Time Scenario View
  11. Soniya R, Britto R. INNOVATIONS IN THERMAL, MANUFACTURING, STRUCTURAL AND ENVIRONMENTAL ENGINEERING: ICITMSEE’24. Comparative analysis of autism spectrum disorder was performed using an EEG signal with the novel boosted trees classifier and SVM classifier View
  12. Kaloforidis N, Kollias K, Radoglou-Grammatikis P, Sarigiannidis P, Fragulis G. ETLTC 2025. Autism Spectrum Disorder Classification in Children Using Eye-Tracking Data and Machine Learning View
  13. Tabanlı İ, Erdem O. 2025 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). Diagnosis of Autism Spectrum Disorder from Eye-Tracking Scanpath Images Using Customized CNN View