AI-based non-invasive imaging technologies for early autism spectrum disorder diagnosis: A short review and future directions

Document Type

Article

Source of Publication

Artificial Intelligence in Medicine

Publication Date

3-1-2025

Abstract

Autism Spectrum Disorder (ASD) is a neurological condition, with recent statistics from the CDC indicating a rising prevalence of ASD diagnoses among infants and children. This trend emphasizes the critical importance of early detection, as timely diagnosis facilitates early intervention and enhances treatment outcomes. Consequently, there is an increasing urgency for research to develop innovative tools capable of accurately and objectively identifying ASD in its earliest stages. This paper offers a short overview of recent advancements in non-invasive technology for early ASD diagnosis, focusing on an imaging modality, structural MRI technique, which has shown promising results in early ASD diagnosis. This brief review aims to address several key questions: (i) Which imaging radiomics are associated with ASD? (ii) Is the parcellation step of the brain cortex necessary to improve the diagnostic accuracy of ASD? (iii) What databases are available to researchers interested in developing non-invasive technology for ASD? (iv) How can artificial intelligence tools contribute to improving the diagnostic accuracy of ASD? Finally, our review will highlight future trends in ASD diagnostic efforts.

ISSN

0933-3657

Publisher

Elsevier BV

Volume

161

Disciplines

Computer Sciences

Keywords

Artificial Intelligence, Autism spectrum disorder, Diagnosis, sMRI

Scopus ID

85216921995

Indexed in Scopus

yes

Open Access

no

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