Published on in Vol 21, No 4 (2019): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13822, first published .
Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study

Journals

  1. Kline A, Voss C, Washington P, Haber N, Schwartz H, Tariq Q, Winograd T, Feinstein C, Wall D. Superpower Glass. GetMobile: Mobile Computing and Communications 2019;23(2):35 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. 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
  4. Kalantarian H, Jedoui K, Dunlap K, Schwartz J, Washington P, Husic A, Tariq Q, Ning M, Kline A, Wall D. The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study. JMIR Mental Health 2020;7(4):e13174 View
  5. Washington P, Park N, Srivastava P, Voss C, Kline A, Varma M, Tariq Q, Kalantarian H, Schwartz J, Patnaik R, Chrisman B, Stockham N, Paskov K, Haber N, Wall D. Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2020;5(8):759 View
  6. 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
  7. Rahman M, Usman O, Muniyandi R, Sahran S, Mohamed S, Razak R. A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder. Brain Sciences 2020;10(12):949 View
  8. Frostig T, Alonim H, Scheingesicht G, Benjamini Y, Golani I. Exploration in the Presence of Mother in Typically and Non-typically Developing Pre-walking Human Infants. Frontiers in Behavioral Neuroscience 2020;14 View
  9. Washington P, Tariq Q, Leblanc E, Chrisman B, Dunlap K, Kline A, Kalantarian H, Penev Y, Paskov K, Voss C, Stockham N, Varma M, Husic A, Kent J, Haber N, Winograd T, Wall D. Crowdsourced privacy-preserved feature tagging of short home videos for machine learning ASD detection. Scientific Reports 2021;11(1) View
  10. Haque M, Rabbani M, Dipal D, Zarif M, Iqbal A, Schwichtenberg A, Bansal N, Soron T, Ahmed S, Ahamed S. Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach. JMIR Medical Informatics 2021;9(6):e29242 View
  11. Kojovic N, Natraj S, Mohanty S, Maillart T, Schaer M. Using 2D video-based pose estimation for automated prediction of autism spectrum disorders in young children. Scientific Reports 2021;11(1) View
  12. Park Y, Hwang S, Yu Y, Kim J, Lee T, Kim H. Screening children at risk for developmental disabilities based on face landmark from video data of mobile-based application: Preliminary Cross-Sectional Study (Preprint). JMIR Pediatrics and Parenting 2021 View
  13. Abdulhay E, Alafeef M, Hadoush H, Arunkumar N. A 64‐channel scheme for autism detection via scaled conjugate gradient‐based neural network classification of electroencephalogram ripples' complexity. Expert Systems 2023;40(4) View
  14. Rabbani M, Haque M, Dipal D, Zarif M, Iqbal A, Schwichtenberg A, Bansal N, Soron T, Ahmed S, Ahamed S. A data-driven validation of mobile-based care (mCARE) project for children with ASD in LMICs. Smart Health 2022;26:100345 View
  15. 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
  16. 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
  17. 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
  18. Rabbani M, Haque M, Das Dipal D, Zarif M, Iqbal A, Schwichtenberg A, Bansal N, Soron T, Ahmed S, Ahamed S. An mCARE study on patterns of risk and resilience for children with ASD in Bangladesh. Scientific Reports 2021;11(1) View
  19. Leo M, Bernava G, Carcagnì P, Distante C. Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions. Sensors 2022;22(3):866 View
  20. Abdulhay E, Alafeef M, Hadoush H, Venkataraman V, Arunkumar N. EMD-based analysis of complexity with dissociated EEG amplitude and frequency information: a data-driven robust tool -for Autism diagnosis- compared to multi-scale entropy approach. Mathematical Biosciences and Engineering 2022;19(5):5031 View
  21. 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
  22. Shih C, Pudipeddi R, Uthayakumar A, Washington P. A Local Community-Based Social Network for Mental Health and Well-being (Quokka): Exploratory Feasibility Study. JMIRx Med 2021;2(4):e24972 View
  23. Dwyer D, Koutsouleris N. Annual Research Review: Translational machine learning for child and adolescent psychiatry. Journal of Child Psychology and Psychiatry 2022;63(4):421 View
  24. Stavropoulos K, Bolourian Y, Blacher J, Moody E. A scoping review of telehealth diagnosis of autism spectrum disorder. PLOS ONE 2022;17(2):e0263062 View
  25. Kamp-Becker I, Tauscher J, Wolff N, Küpper C, Poustka L, Roepke S, Roessner V, Heider D, Stroth S. Is the Combination of ADOS and ADI-R Necessary to Classify ASD? Rethinking the “Gold Standard” in Diagnosing ASD. Frontiers in Psychiatry 2021;12 View
  26. Alam S, Raja P, Gulzar Y, Lakshmanna K. Investigation of Machine Learning Methods for Early Prediction of Neurodevelopmental Disorders in Children. Wireless Communications and Mobile Computing 2022;2022:1 View
  27. 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
  28. 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
  29. Wolff N, Kohls G, Mack J, Vahid A, Elster E, Stroth S, Poustka L, Kuepper C, Roepke S, Kamp-Becker I, Roessner V. A data driven machine learning approach to differentiate between autism spectrum disorder and attention-deficit/hyperactivity disorder based on the best-practice diagnostic instruments for autism. Scientific Reports 2022;12(1) View
  30. Saranya A, Anandan R. Facial Action Coding and Hybrid Deep Learning Architectures for Autism Detection. Intelligent Automation & Soft Computing 2022;33(2):1167 View
  31. 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
  32. Kohli M, Kar A, Sinha S. The Role of Intelligent Technologies in Early Detection of Autism Spectrum Disorder (ASD): A Scoping Review. IEEE Access 2022;10:104887 View
  33. 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
  34. Prakash V, Kohli M, Prathosh A, Juneja M, Gupta M, Sairam S, Sitaraman S, Bangalore A, Kommu J, Saini L, Utage P, Goyal N. Video‐based real‐time assessment and diagnosis of autism spectrum disorder using deep neural networks. Expert Systems 2023 View
  35. 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
  36. Prakash V, Kohli M, Kohli S, Prathosh A, Wadhera T, Das D, Panigrahi D, Kommu J. Computer Vision-Based Assessment of Autistic Children: Analyzing Interactions, Emotions, Human Pose, and Life Skills. IEEE Access 2023;11:47907 View
  37. Almufareh M, Tehsin S, Humayun M, Kausar S. Intellectual Disability and Technology: An Artificial Intelligence Perspective and Framework. Journal of Disability Research 2023;2(4) View
  38. Rasul R, Saha P, Bala D, Karim S, Abdullah M, Saha B. An evaluation of machine learning approaches for early diagnosis of autism spectrum disorder. Healthcare Analytics 2024;5:100293 View
  39. Washington P. A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138 View
  40. Reinhart L, Bischops A, Kerth J, Hagemeister M, Heinrichs B, Eickhoff S, Dukart J, Konrad K, Mayatepek E, Meissner T. Artificial intelligence in child development monitoring: A systematic review on usage, outcomes and acceptance. Intelligence-Based Medicine 2024;9:100134 View
  41. Kohli M, Kar A, Sinha S, Kohli S. Stakeholder perception towards a machine‐learning‐based digital platform for detection and management of autism spectrum disorder. Expert Systems 2024 View
  42. 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
  43. Hwang S, Yu Y, Kim J, Lee T, Park Y, Kim H. A Study on the Screening of Children at Risk for Developmental Disabilities Using Facial Landmarks Derived From a Mobile-Based Application. Psychiatry Investigation 2024;21(5):496 View
  44. Alam M, Sajib M, Rahman F, Ether S, Hanson M, Sayeed A, Akter E, Nusrat N, Islam T, Raza S, Tanvir K, Chisti M, Rahman Q, Hossain A, Layek M, Zaman A, Rana J, Rahman S, Arifeen S, Rahman A, Ahmed A. Implications of Big Data Analytics, AI, Machine Learning, and Deep Learning in the Health Care System of Bangladesh: Scoping Review. Journal of Medical Internet Research 2024;26:e54710 View
  45. Nabil M, Akram A, Fathalla K. Applying machine learning on home videos for remote autism diagnosis: Further study and analysis. Health Informatics Journal 2021;27(1) View

Books/Policy Documents

  1. Dhawale C, Dhawale K, Dubey R. Deep Learning Techniques and Optimization Strategies in Big Data Analytics. View
  2. Ajaypradeep N, Sasikala R. Education and Technology Support for Children and Young Adults With ASD and Learning Disabilities. View
  3. Farzana W, Sarker F, Hossain Q, Chau T, Mamun K. HCI International 2020 – Late Breaking Posters. View
  4. Maitra S, Akter N, Zahan Mithila A, Hossain T, Shafiul Alam M. Progress in Advanced Computing and Intelligent Engineering. View
  5. Jindal M, Chakraborty A, Bajal E, Sharma S. Data Driven Approach Towards Disruptive Technologies. View
  6. Rabbani M, Haque M, Das Dipal D, Zarif M, Iqbal A, Akhter S, Parveen S, Rasel M, Soron T, Bansal N, Schwichtenberg A, Ahmed S, Ahamed S. AI Applications for Disease Diagnosis and Treatment. View
  7. Dahiya A, Bertollo J, McDonnell C, Scarpa A. Neural Engineering Techniques for Autism Spectrum Disorder, Volume 2. View
  8. Rabbani M, Haque M, Das Dipal D, Zarif M, Iqbal A, Schwichtenberg A, Bansal N, Soron T, Ahmed S, Ahamed S. Pervasive Computing Technologies for Healthcare. View
  9. Kohli M, Kar A, Prakash V, Prathosh A. Neural Information Processing. View
  10. Beani E, Filogna S, Cioni G, Sgandurra G. Family-Centered Care in Childhood Disability. View