Published on in Vol 7, No 4 (2020): April

Preprints (earlier versions) of this paper are available at, first published .
The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study

The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study

The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study


  1. Nag A, Haber N, Voss C, Tamura S, Daniels J, Ma J, Chiang B, Ramachandran S, Schwartz J, Winograd T, Feinstein C, Wall D. Toward Continuous Social Phenotyping: Analyzing Gaze Patterns in an Emotion Recognition Task for Children With Autism Through Wearable Smart Glasses. Journal of Medical Internet Research 2020;22(4):e13810 View
  2. Washington P, Leblanc E, Dunlap K, Penev Y, Kline A, Paskov K, Sun M, Chrisman B, Stockham N, Varma M, Voss C, Haber N, Wall D. Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition. Journal of Personalized Medicine 2020;10(3):86 View
  3. Leblanc E, Washington P, Varma M, Dunlap K, Penev Y, Kline A, Wall D. Feature replacement methods enable reliable home video analysis for machine learning detection of autism. Scientific Reports 2020;10(1) View
  4. Abououf M, Otrok H, Mizouni R, Singh S, Damiani E. How Artificial Intelligence and Mobile Crowd Sourcing are Inextricably Intertwined. IEEE Network 2021;35(3):252 View
  5. Banerjee A, Mutlu O, Kline A, Surabhi S, Washington P, Wall D. Training and Profiling a Pediatric Facial Expression Classifier for Children on Mobile Devices: Machine Learning Study. JMIR Formative Research 2023;7:e39917 View
  6. Washington P, Kalantarian H, Kent J, Husic A, Kline A, Leblanc E, Hou C, Mutlu O, Dunlap K, Penev Y, Varma M, Stockham N, Chrisman B, Paskov K, Sun M, Jung J, Voss C, Haber N, Wall D. Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study. JMIR Pediatrics and Parenting 2022;5(2):e26760 View
  7. Deveau N, Washington P, Leblanc E, Husic A, Dunlap K, Penev Y, Kline A, Mutlu O, Wall D. Machine learning models using mobile game play accurately classify children with autism. Intelligence-Based Medicine 2022;6:100057 View
  8. Lyakso E, Frolova O, Grigoriev A, Filatova Y, Makhnytkina O. Recognition of Emotional States of Children with down Syndrome by Facial Expression: Perceptual and Automatic Analysis of Dynamic Images. Experimental Psychology (Russia) 2022;15(3):140 View
  9. Lakkapragada A, Kline A, Mutlu O, Paskov K, Chrisman B, Stockham N, Washington P, Wall D. The Classification of Abnormal Hand Movement to Aid in Autism Detection: Machine Learning Study. JMIR Biomedical Engineering 2022;7(1):e33771 View
  10. Sleiman E, Mutlu O, Surabhi S, Husic A, Kline A, Washington P, Wall D. Deep Learning-Based Autism Spectrum Disorder Detection Using Emotion Features From Video Recordings (Preprint). JMIR Biomedical Engineering 2022 View
  11. Varma M, Washington P, Chrisman B, Kline A, Leblanc E, Paskov K, Stockham N, Jung J, Sun M, Wall D. Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods. Journal of Medical Internet Research 2022;24(2):e31830 View
  12. Washington P, Chrisman B, Leblanc E, Dunlap K, Kline A, Mutlu C, Stockham N, Paskov K, Wall D. Crowd annotations can approximate clinical autism impressions from short home videos with privacy protections. Intelligence-Based Medicine 2022;6:100056 View
  13. Chi N, Washington P, Kline A, Husic A, Hou C, He C, Dunlap K, Wall D. Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study. JMIR Pediatrics and Parenting 2022;5(2):e35406 View
  14. Al-Saadi A, Al-Thani D. Mobile Application to identify and recognize emotions for children with autism: A systematic review. Frontiers in Child and Adolescent Psychiatry 2023;2 View
  15. Chen S, Huang L, Liu G, Kang J, Qian Q, Wang J, Wang R, Zheng L, Wang H, Ou P. Acupuncture Ameliorated Behavioral Abnormalities in the Autism Rat Model via Pathways for Hippocampal Serotonin. Neuropsychiatric Disease and Treatment 2023;Volume 19:951 View
  16. Alqahtani A, Gufran K, Alsakr A, Alnufaiy B, Al Ghwainem A, Bin Khames Y, Althani R, Almuthaybiri S. Oral Healthcare Practices and Awareness among the Parents of Autism Spectrum Disorder Children: A Multi-Center Study. Children 2023;10(6):978 View
  17. Liu X, Zhao W, Qi Q, Luo X. A Survey on Autism Care, Diagnosis, and Intervention Based on Mobile Apps: Focusing on Usability and Software Design. Sensors 2023;23(14):6260 View
  18. Washington P, Wall D. A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism. Annual Review of Biomedical Data Science 2023;6(1):211 View
  19. Sun Y, Kargarandehkordi A, Slade C, Jaiswal A, Busch G, Guerrero A, Phillips K, Washington P. Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study. JMIR Research Protocols 2024;13:e46493 View
  20. Jaiswal A, Washington P. Using #ActuallyAutistic on Twitter for precision diagnosis of Autism Spectrum Disorder (ASD) (Preprint). JMIR Formative Research 2023 View
  21. Jaiswal A, Kruiper R, Rasool A, Nandkeolyar A, Wall D, Washington P. Digitally Diagnosing Multiple Developmental Delays Using Crowdsourcing Fused With Machine Learning: Protocol for a Human-in-the-Loop Machine Learning Study. JMIR Research Protocols 2024;13:e52205 View
  22. Washington P. A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138 View
  23. Kargarandehkordi A, Kaisti M, Washington P. Personalization of Affective Models Using Classical Machine Learning: A Feasibility Study. Applied Sciences 2024;14(4):1337 View
  24. Jiran Meitei A, Mohapatra B, Khundrakpam B, Tawfeeq Alee N, Chauhan G. Role of AI/ML in the Study of Autism Spectrum Disorders: A Bibliometric Analysis. Journal of Technology in Behavioral Science 2024 View

Books/Policy Documents

  1. Jankova D, Andova I, Bajrami M, Vrangalovski M, Ilijoski B, Lameski P, Dineva K. ICT Innovations 2022. Reshaping the Future Towards a New Normal. View