ArticleJournal of autism and developmental disorders2024
Machine Learning Differentiation of Autism Spectrum Sub-Classifications.
Article in Journal of autism and developmental disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Finding the forest in the trees: Using machine learning and online cognitive and perceptual measures to predict adult autism diagnosis.Translational psychiatry · 2026Article
- A Brief Observation to Screen Autism in Toddlers and Predict Developmental Trajectory.Journal of pediatrics. Clinical practice · 2025Article
- Review of Autism Spectrum Disorder (ASD): Epidemiology, Aetiology, Pathology, and Pharmacological Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- An Adaptive Transfer Learning Framework for Multimodal Autism Spectrum Disorder Diagnosis.Life (Basel, Switzerland) · 2025Article
- Machine learning to evaluate the effects of non-clinical social determinant features in predicting colorectal Cancer mortality in a medically underserved Appalachian population.Scientific reports · 2025Article
- Parent-Led Applied Behavior Analysis to Impact Clinical Outcomes for Individuals on the Autism Spectrum: Retrospective Chart Review.JMIR pediatrics and parenting · 2024Article
- Family-Centric Applied Behavior Analysis Promotes Sustained Treatment Utilization and Attainment of Patient Goals.Cureus · 2024Article
- Machine Learning Approach with Harmonized Multinational Datasets for Enhanced Prediction of Hypothyroidism in Patients with Type 2 Diabetes.Diagnostics (Basel, Switzerland) · 2024Article
- Machine Learning Approach for Improved Longitudinal Prediction of Progression from Mild Cognitive Impairment to Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDisorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which can make diagnosing a disorder on the autism spectrum complex. We evaluated machine learning to classify individuals as having one of three disorders of the autism spectrum under DSM-IV, or as non-spectrum.
methodsWe employed machine learning to analyze retrospective data from 38,560 individuals. Inputs encompassed clinical, demographic, and assessment data.
resultsThe algorithm achieved AUROCs ranging from 0.863 to 0.980. The model correctly classified 80.5% individuals; 12.6% of individuals from this dataset were misclassified with another disorder on the autism spectrum.
conclusionMachine learning can classify individuals as having a disorder on the autism spectrum or as non-spectrum using minimal data inputs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.