Supervised Machine Learning for a Novel Autism Prediction Tool in Adults

This publication is included in the Autistic Autism Scholarship Project. one author of this publication is identified as autistic in the project.

About the autistic author marker

Brandsen, S., Hallur, S., Andrews, I., Naqvi, M., Zhou, S., Boheler, J., & Chandrasekhar, T. (2024). Supervised Machine Learning for a Novel Autism Prediction Tool in Adults [Preprint]. Center for Open Science. https://doi.org/10.31219/osf.io/89r3u

Publication date: 13 Dec 2024 Added to AutiHub: 5 Jul 2026 Type: Preprint Article language: English

This publication is integrated into AutiHub through:

Authors

Publication authors
7
Publication authors identified as autistic
1 / 7 (14.3%)

Abstract

For many late-identified autistic adults, the realization that they are autistic can be a key first step to accessing supportive resources and accommodations and developing self-understanding. We introduce a novel screening tool for autistic traits designed primarily by autistic adults. It includes options to assess masking, sensory processing differences, commonly co-occurring medical or mental health conditions, and questions about social and communication differences and repetitive behavior. We used a simple supervised machine learning algorithm to generate a score predicting whether the individual is autistic. Our results indicate that this algorithm was able to distinguish respondents who are non-autistic from respondents who self-reported being formally diagnosed as autistic. Additionally, our algorithm remained effective in identifying autism in respondents with other under-represented identities. Finally, we separately analyzed the responses of self-identified autistic individuals and found a high degree of overlap in the responses of self-identified and formally diagnosed autistic respondents.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 2 Oct 2026 13:58.

Cited references
22
With a DOI
21
Without a DOI, from raw bibliography text
0
4 / 22 (18.2%) cited references include at least one author identified as autistic.
References with data to complete
0 / 22 (0.0%)
References with detected author names
22 / 22 (100.0%)
Without detected author names
0
Without a structured title
0
Without a stable identifier
0
References with raw author names still to review
0
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
108
From DOI or external metadata
108
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
0
26 / 108 (24.1%) names are linked to an author already present in AutiHub. 82 / 108 (75.9%) names are not yet linked.
Names linked to a person identified as autistic
6 / 108 (5.6%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 6 / 26 (23.1%). Distinct people identified as autistic: 6 / 106 (5.7%).
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    OpenAlex
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    OpenAlex
  8. Camilla Gesi , Giovanni Migliarese , Sara Torriero , Martina Capellazzi , Anna Caterina Omboni , Giancarlo Cerveri et al. (2021). Gender Differences in Misdiagnosis and Delayed Diagnosis among Adults with Autism Spectrum Disorder with No Language or Intellectual Disability . Brain Sciences, 11(7), 912. MDPI AG.
    OpenAlex
  9. Paula Corscadden , Ann Marie Casserly (2021). Identification of Autism in Girls: Role of Trait Subtleties, Social Acceptance and Masking. REACH: Journal of Inclusive Education in Ireland, 34(1).
    Type: Article OpenAlex: https://openalex.org/W3199030035
    OpenAlex
  10. Brandon S. Aylward , Diana E. Gal-Szabo , Sharief Taraman (2021). Racial, Ethnic, and Sociodemographic Disparities in Diagnosis of Children with Autism Spectrum Disorder . Journal of Developmental & Behavioral Pediatrics, 42(8), 682-689. Ovid Technologies (Wolters Kluwer Health).
    OpenAlex
  11. Matthew de Broize , Kiah Evans , Andrew Whitehouse , John Wray , Valsamma Eapen , Anna Urbanowicz (2022). Exploring the Experience of Seeking an Autism Diagnosis as an Adult . Autism in Adulthood, 4(2), 130-140. SAGE Publications.
    OpenAlex
  12. Allison P Fisher , James D Lynch , Farrah M Jacquez , Monica J Mitchell , Kelly I Kamimura-Nishimura , Shari L Wade (2023). A systematic review examining caregivers’ of color experiences with the diagnostic process of autism spectrum disorder . Autism, 27(4), 876-889. SAGE Publications.
    OpenAlex
  13. Maria Ferrara , Giorgia Franchini , Melissa Funaro , Marcello Cutroni , Beatrice Valier , Tommaso Toffanin et al. (2022). Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment . Current Psychiatry Reports, 24(12), 925-936. Springer Science and Business Media LLC.
    OpenAlex
  14. Gayle L. Overton , Ferran Marsà-Sambola , Rachael Martin , Penny Cavenagh (2024). Understanding the Self-identification of Autism in Adults: a Scoping Review . Review Journal of Autism and Developmental Disorders, 11(4), 682-702. Springer Science and Business Media LLC.
    OpenAlex
  15. Alessandro Pigoni , Giuseppe Delvecchio , Nunzio Turtulici , Domenico Madonna , Pietro Pietrini , Luca Cecchetti et al. (2024). Machine learning and the prediction of suicide in psychiatric populations: a systematic review . Translational Psychiatry, 14(1), 140-140. Springer Science and Business Media LLC.
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  16. Harlee Onovbiona , Lauren Quetsch , Emily-Anne Del Rosario (2025). Exploring Factors of Diagnostic Timing Among Black Autistic Youth . Journal of Autism and Developmental Disorders, 55(4), 1438-1449. Springer Science and Business Media LLC.
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  17. Sheharyar Khan , Sanay Muhammad Umar Saeed , Jaroslav Frnda , Aamir Arsalan , Rashid Amin , Rahma Gantassi et al. (2024). A machine learning based depression screening framework using temporal domain features of the electroencephalography signals . PLOS ONE, 19(3), e0299127. Public Library of Science (PLoS).
    OpenAlex
  18. Zachary Gallin , Ana M. Kolevzon , Abraham Reichenberg , Sidney H. Hankerson , Alexander Kolevzon , Alexander Kolevzon et al. (2025). Racial Differences in the Prevalence of Autism Spectrum Disorder: A Systematic Review . Journal of Autism and Developmental Disorders, 55(9), 3364-3377. Springer Science and Business Media LLC.
    OpenAlex