Evidence map›Paper›PMID 41014972›Full record

SynthesisEBioMedicine2025

Artificial intelligence for tracking social behaviours and supporting an autism spectrum disorder diagnosis: systematic review and meta-analysis.

Carter Sun, Alistair McEwan, Kelsie A Boulton, Eleni Andrea Demetriou, Ayesha K Sadozai, Amit Lampit, Adam J Guastella

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in EBioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Carter SunClinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Australia; Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Australia; School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Australia.
Alistair McEwanChild Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Australia; School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Australia.
Kelsie A BoultonClinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Australia; Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Australia.
Eleni Andrea DemetriouClinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Australia; Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Australia.
Ayesha K SadozaiClinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Australia; Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Australia.
Amit LampitDepartment of Psychiatry, University of Melbourne, Melbourne, Australia.
Adam J GuastellaClinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Australia; Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Australia. Electronic address: adam.guastella@sydney.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) holds promise for developing tools that can track social behaviours and support clinical assessments and outcomes in Autism Spectrum Disorders (ASD). This review evaluated existing AI algorithms for extracting facial information during social interaction assessments and contributing to diagnostic accuracy for ASD assessment and response to therapy.

methodsSystematic review of studies on human participants with an ASD diagnosis, sourced from Medline, Embase, Scopus, Web of Science, IEEE Xplore, and ACM Digital Library, evaluated the diagnostic accuracy of AI algorithms in ASD classification and their use in tracking social development through facial information for clinical application in social interactions. Bivariate and multi-level models addressed dependencies, heterogeneity, moderators (modalities, algorithms, tasks), and applied robust variance estimation. Publication bias was evaluated with funnel plots. The QUADAS-2 tool assessed the risk of bias and applicability. This study was registered on PROSPERO (CRD42021249905).

findingsOf 40,570 studies identified, 38 met the review criteria, and seven provided sufficient data for meta-analysis. The pooled diagnostic odds ratio of 15.917 (95% CI [4.775-53.059]), and bivariate analysis estimated an area under the receiver operating characteristic curve of 0.862. Accuracy improved with facial features, unstructured play, support vector machines, and decision tree-based algorithms. AI methods can analyse social behaviours, including eye gaze on social stimuli, emotional expression, and joint attention in ASD assessments. AI-enabled robots have also been used to guide therapy.

interpretationThis study shows that AI can accurately and objectively augment ASD assessments, track social behaviours, and enhance therapy outcomes. Further validation in diverse populations is needed to ensure clinical applicability and ethical use.

fundingNone.

Indexed as

Artificial IntelligenceAutism Spectrum DisorderSocial BehaviorAlgorithmsHumansROC CurveAutism spectrum disordersClinical diagnosisFacial informationMeta-analysisSocial interaction assessmentSystematic review

Identifiers

PMID41014972
PMCPMC12509731

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.