Published on in Vol 21, No 5 (2019): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13668, first published .
Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks

Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks

Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks

Journals

  1. 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
  2. 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
  3. 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
  4. 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
  5. Zhou L, Parmanto B. Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(4):e15075 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. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. Ben-Sasson A, Jacobs K, Ben-Sasson E. Early childhood tracking application: Correspondence between crowd-based developmental percentiles and clinical tools. Health Informatics Journal 2023;29(1):146045822311646 View
  16. 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
  17. Titov A, Drouin S, Kersten-Oertel M. Connect Brain, a Mobile App for Studying Depth Perception in Angiography Visualization: Gamification Study. JMIR Neurotechnology 2023;2:e45828 View
  18. 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
  19. Washington P. A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138 View
  20. Lalvani S, Katsaggelos A. Crowdsourcing with the drift diffusion model of decision making. Scientific Reports 2024;14(1) View