Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Artificial Intelligence: the "Trait D'Union" in Different Analysis Approaches of Autism Spectrum Disorder Studies.

Current medicinal chemistry - 1 Jan 2021

Marciano Francesca, Venutolo Giorgia, Ingenito Carminia Marina, Verbeni Antonella, Terracciano Concetta, Plunk Elizabeth, Garaci Francesco, Cavallo Armando, Fasano Alessio

Abstract excerpt

Autistic Spectrum Disorder (ASD) is a neurodevelopmental condition affecting approximately 1 out of 70 (range 1:59 - 1:89) children worldwide. It is characterized by a delay in cognitive capabilities, repetitive and restricted behaviors and deficit in communication and social interaction. Several factors seem to be associated with ASD development; its heterogeneous nature makes the diagnosis difficult and slow...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Artificial Intelligence
Share to Autism Spectrum Disorder

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Machine Learning

Share to Neuroimaging

Share to Phenotype

Source

Identifiers

PMID: 33538662
DOI: 10.2174/0929867328666210203205221

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Artificial Intelligence: the "Trait D'Union" in Different Analysis Approaches of Autism Spectrum Disorder Studies.PMID 33538662Read ↗

The role of machine learning in autism spectrum disorder assessment and management.Semantic proximity Read ↗

A new computational intelligence approach to detect autistic features for autism screening.Semantic proximity Read ↗

Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning AlgorithmsSemantic proximity Read ↗

Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles.Semantic proximity Read ↗

Automated Classification of Restrictive and Repetitive Behaviors in Autistic ChildrenSemantic proximity Read ↗

WITHDRAWN: Bridging the Gap: Explainable AI for Autism Diagnosis and Parental Support with TabPFNMix and SHAPSemantic proximity Read ↗

A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism.Semantic proximity Read ↗

End-to-End Explainable AI: Derived Theory-of-Mind Fingerprints to Distinguish Between Autistic and Typically developing and Social Symptom SeveritySemantic proximity Read ↗

Ensemble statistical and subspace clustering model for analysis of autism spectrum disorder phenotypes.Semantic proximity Read ↗

Wavelets Based Feature Extraction With PCA For Predicting Autism In Neonates Using Navïe Bayes ClassifierSemantic proximity Read ↗

Translational Study of using FOCM/TS Metabolites for Supporting Autism Spectrum Disorder DiagnosisSemantic proximity Read ↗

Augmentative Semi-Supervised Learning for Autism Screening: A Novel FrameworkSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.