• Accelerating autism spectrum d...

Treffer: Accelerating autism spectrum disorder care: A rapid review of data science applications in diagnosis and intervention.

Title:
Accelerating autism spectrum disorder care: A rapid review of data science applications in diagnosis and intervention.
Authors:
Ganggayah MD; School of Business, Monash University Malaysia, Malaysia. Electronic address: moganadarshini.ganggayah@monash.edu., Zhao D; School of Business, Monash University Malaysia, Malaysia., Liew EJY; School of Business, Monash University Malaysia, Malaysia., Mohd Nor NA; School of Pharmacy, Monash University Malaysia, Malaysia., Paramasivam T; Garden International School, Mont Kiara, Kuala Lumpur, Malaysia., Lee YY; Shining Star Learning Hub, Taman Bukit Desa, Kuala Lumpur, Malaysia., Abu Hasan NI; School of Mathematical Sciences Studies, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Perlis Branch, Arau Campus, Malaysia., Shaharuddin S; School of Pharmacy, Monash University Malaysia, Malaysia.
Source:
Asian journal of psychiatry [Asian J Psychiatr] 2025 Jun; Vol. 108, pp. 104498. Date of Electronic Publication: 2025 Apr 13.
Publication Type:
Journal Article; Review
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101517820 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-2026 (Electronic) Linking ISSN: 18762018 NLM ISO Abbreviation: Asian J Psychiatr Subsets: MEDLINE
Imprint Name(s):
Original Publication: [Amsterdam] : Elsevier
MeSH Terms:
Autism Spectrum Disorder*/diagnosis , Autism Spectrum Disorder*/therapy , Data Science*/methods , Machine Learning* , Big Data* , Natural Language Processing*, Humans
Contributed Indexing:
Keywords: Autism spectrum disorder; Data science; Deep learning; IoT; Machine learning; Natural language processing
Entry Date(s):
Date Created: 20250419 Date Completed: 20250530 Latest Revision: 20250530
Update Code:
20260130
DOI:
10.1016/j.ajp.2025.104498
PMID:
40252472
Database:
MEDLINE

Weitere Informationen

Integrating data science techniques, including machine learning, natural language processing, and big data analytics, has revolutionized the diagnosis and intervention landscape for Autism Spectrum Disorder (ASD). This rapid review examines these approaches' current applications, benefits, limitations, and ethical considerations while identifying key research gaps and future directions. Data-driven methodologies offer significant advantages, such as enhanced diagnostic accuracy, personalized interventions, and increased accessibility, particularly in resource-limited settings. However, challenges like data quality, algorithmic bias, and interpretability hinder widespread implementation. Additionally, ethical concerns regarding privacy, consent, and equity necessitate careful navigation. Despite these advancements, substantial research gaps remain, including the lack of diverse datasets, limited longitudinal studies, and insufficient generalizability across populations. Future studies must prioritize addressing these gaps by fostering collaboration, ensuring ethical transparency, and developing inclusive, scalable solutions to improve patient outcomes. This review underscores the transformative potential of data science in accelerating ASD care while emphasizing the need for continued innovation and responsible application.
(Copyright © 2025 The Authors. Published by Elsevier B.V. All rights reserved.)

Declaration of Competing Interest The authors have no competing interests to declare.