This paper is in the following e-collection/theme issue:

Children and Youth with Disabilities (60) Clinical Informatics (1142) Autism Spectrum Disorder (ASD) (125) Machine Learning (1694) Artificial Intelligence (1676) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (94)

Published on in Vol 5, No 2 (2022): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35406, first published .
Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study

Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study

Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study

Authors of this article:

Nathan A Chi1 Author Orcid Image ;   Peter Washington2 Author Orcid Image ;   Aaron Kline1 Author Orcid Image ;   Arman Husic1 Author Orcid Image ;   Cathy Hou3 Author Orcid Image ;   Chloe He4 Author Orcid Image ;   Kaitlyn Dunlap1 Author Orcid Image ;   Dennis P Wall1, 4, 5 Author Orcid Image
Article Authors Cited by (27) Tweetations (20) Metrics

Journals

  1. 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
  2. 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
  3. 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
  4. Idrisoglu A, Dallora A, Anderberg P, Berglund J. Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review. Journal of Medical Internet Research 2023;25:e46105 View
  5. 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
  6. Jaiswal A, Washington P. Using #ActuallyAutistic on Twitter for Precision Diagnosis of Autism Spectrum Disorder: Machine Learning Study. JMIR Formative Research 2024;8:e52660 View
  7. 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
  8. Sfakianaki A, Nicolaidis K, Kafentzis G. Temporal, spectral and amplitude characteristics of the Greek fricative /s/ in hearing-impaired and normal-hearing speech. Clinical Linguistics & Phonetics 2024;38(8):720 View
  9. Washington P. A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138 View
  10. Toki E, Pange J, Tatsis G, Plachouras K, Tsoulos I. Utilizing Constructed Neural Networks for Autism Screening. Applied Sciences 2024;14(7):3053 View
  11. Rogers H, Hseu A, Kim J, Silberholz E, Jo S, Dorste A, Jenkins K. Voice as a Biomarker of Pediatric Health: A Scoping Review. Children 2024;11(6):684 View
  12. Lin K, Washington P. Multimodal deep learning for dementia classification using text and audio. Scientific Reports 2024;14(1) View
  13. Ruan L, Chen G, Yao M, Li C, Chen X, Luo H, Ruan J, Zheng Z, Zhang D, Liang S, Lü M. Brain functional gradient and structure features in adolescent and adult autism spectrum disorders. Human Brain Mapping 2024;45(11) View
  14. Arimoto Y, Oishi D, Okubo M. A comparison between crowdsourcing and in-person listening tests on emotion rating for spontaneous screams and shouts. Acoustical Science and Technology 2025;46(2):125 View
  15. Jin L, Cui H, Zhang P, Cai C. Early diagnostic value of home video–based machine learning in autism spectrum disorder: a meta-analysis. European Journal of Pediatrics 2024;184(1) View
  16. Dong L, Hirayama H, Zheng X, Masukawa K, Miyashita M. Using voice recognition and machine learning techniques for detecting patient‐reported outcomes from conversational voice in palliative care patients. Japan Journal of Nursing Science 2025;22(1) View
  17. Eni M, Zigel Y, Ilan M, Michaelovski A, Golan H, Meiri G, Menashe I, Dinstein I. Reliably quantifying the severity of social symptoms in children with autism using ASDSpeech. Translational Psychiatry 2025;15(1) View
  18. Bertamini G, Furlanello C, Chetouani M, Cohen D, Venuti P. Automated segmentation of child-clinician speech in naturalistic clinical contexts. Research in Developmental Disabilities 2025;157:104906 View

Books/Policy Documents

  1. Ramos V, Mondéjar T, Ferrández A, Peral J, Gil D, Mora H. Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023). View
  2. Mouad E, Hanae B, Khalid M. Engineering Applications of Neural Networks. View

Conference Proceedings

  1. Kurniawan W, Gunawan P, Aquarini N. 2023 International Conference on Data Science and Its Applications (ICoDSA). Comparison of the Keras-LSTM Algorithms for Classifying Autism Spectrum Disorder Using Facial Images View
  2. 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
  3. Kumar R, Bordoloi D, Shrivastava A, Kumar C, Kumari V, Kumar A. 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON). Behavioral and Clinical Data Analysis for Autism Spectrum Disorder Screening with Machine Learning View
  4. Al-Nashashibi M, Alauthman M, Hadi W. 2024 2nd International Conference on Cyber Resilience (ICCR). Machine Learning for Enhanced Autism Screening: A Comparative Evaluation of Classification Algorithms View
  5. Ayyadurai M, Sujatha K, Deeptha R, Preethi D, Dinesh M. 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). Exploring Data Mining Techniques for Early Autism Detection using Random Forest Algorithm View
  6. D T, Subbiah S, Premkumar R. 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS). A Multimodal Diagnostic Framework for Autism Spectrum Disorder Using Deep Learning: An In-Depth Exploration View
  7. Lai Y, Chen A. 2024 IEEE International Conference on Big Data (BigData). Using speech characteristics from children’s story narratives to detect autistic tendencies through deep learning methods View