Tag: Autism

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Artificial intelligence for autism spectrum disorder: advances in diagnosis, behavior analysis and educational support

IntroductionArtificial intelligence has become an increasingly relevant field of research in the study of Autism Spectrum Disorder (ASD), offering novel technological approaches for the analysis, detection, and support of individuals on the autism spectrum. The aim of this study was to systematically review recent scientific literature examining the application of artificial intelligence in ASD.MethodsThe review was conducted following the PRISMA 2020 guidelines. Searches were performed in PubMed, Scopus, Dialnet, and Google Scholar, including studies published between 2019 and 2025. After applying predefined inclusion and exclusion criteria, 18 empirical studies were included in the final analysis. Methodological quality and risk of bias were assessed using Joanna Briggs Institute critical appraisal tools adapted to the methodological design of each study.ResultsCurrent research focuses primarily on four areas: early detection and diagnostic support, automated analysis of behavioral and social patterns, AI-based educational technologies, and communication support systems. Although the reviewed studies demonstrate promising advances in machine learning, computer vision, and natural language processing, important methodological limitations remain, particularly regarding external validation, dataset representativeness, and heterogeneity of performance indicators.DiscussionOverall, artificial intelligence shows considerable potential for supporting diagnosis, education, and communication in ASD; however, greater methodological robustness, transparency, and ethical safeguards remain necessary before broader implementation in real clinical and educational settings.
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Advancing Clinical Translational Research for Profound Autism

Autism Spectrum Disorder (ASD) has emerged as a key battleground in the federal assault on science. US government leaders have systematically ignored expert advice, reanimated baseless claims about the causal role of vaccines, forwarded thinly supported hypotheses blaming ASD on parental behavior, and promoted unsubstantiated treatments. This barrage comes at a time when the prospects for dramatic near-term advances in clinical translation, particularly for the severe end of the ASD spectrum, have never been greater.

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Gut microbiome dynamics in autism: a prospective nested case–control study demonstrates microbial-clinical associations following rehabilitation interventions

BackgroundChildren with autism spectrum disorder (ASD) commonly exhibit gut microbiota dysbiosis and metabolic abnormalities, yet the mechanisms linking these changes to clinical symptoms remain unclear.ObjectiveThis study employed a nested case–control design and multi-omics approaches to evaluate the effects of rehabilitation intervention on clinical symptoms and gut microbiota in children with ASD, identify distinct microbial-metabolic signatures, and explore their mechanistic links with sleep disorders and developmental abilities.MethodsWithin a prospectively established pediatric cohort (n = 45), we implemented a nested case–control design including 26 ASD children (18 males, 8 females; mean age 61.79 ± 11.15 months) and 19 age- and sex-matched healthy controls. All ASD participants received standardized rehabilitation therapy (2 h/day, 5 days/week for 6 months) comprising occupational therapy and cognitive-linguistic training. Primary outcomes included comprehensive clinical assessments [Griffiths Development Scales-Chinese (GDS-C), Children’s Sleep Habits Questionnaire (CSHQ), Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS)] and longitudinal multi-omics analysis (metagenomic sequencing and LC–MS-based metabolomics). Association analyses were performed with FDR correction (q < 0.05).ResultsFollowing the 6-month rehabilitation intervention, significant clinical improvements were observed in sleep quality (CSHQ total and subscores) and developmental performance (GDS-C). Multi-omics profiling revealed distinct biological signatures in ASD children compared to healthy controls, characterized by elevated Intestinibacter_bartlettii and reduced levels of ornithine and siderophore nonribosomal peptide biosynthesis. Crucially, correlation analysis demonstrated that, after FDR correction, ornithine levels were significantly positively correlated with multiple GDS-C developmental domains, while tyrosine was associated with parasomnias. These findings establish a potential mechanistic link where amino acid metabolism connects gut microbial shifts to clinical phenotypes.ConclusionThis study demonstrates that rehabilitation intervention synchronously ameliorates clinical symptoms and modulates the gut-metabolic profile in ASD. The identified associations between specific metabolites (ornithine and tyrosine) and clinical outcomes suggest a metabolic mechanism underlying the gut-brain axis, highlighting the potential of these metabolites as biomarkers for therapeutic monitoring. Further large-scale studies are needed to validate these findings.