ArticleJournal of autism and developmental disorders2025
Perceptions of Special Education Professionals in the Kingdom of Saudi Arabia Regarding the Integration of Artificial Intelligence in Diagnosing Autism Spectrum Disorder.
Article in Journal of autism and developmental disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Autism spectrum disorder in Saudi Arabia: Clinical dynamics from a multi-center study.Saudi medical journal · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Autism spectrum disorder (ASD) diagnosis often presents challenges due to its complexity and reliance on subjective clinical assessments, potentially leading to delays in identification and intervention. Artificial intelligence (AI) holds significant promise for transforming healthcare, including the potential to improve the accuracy, efficiency, and timeliness of ASD diagnosis. This study investigated the perspectives of 423 specialists in special education across the Kingdom of Saudi Arabia (KSA) on the requirements and challenges associated with integrating AI technologies into the ASD diagnostic process. Utilizing a descriptive survey methodology and a authors-developed questionnaire, we explored specialists' perceptions of AI implementation's financial, human, and regulatory aspects. According to our research, financial, human, and regulatory resources are seen to be crucial for a successful AI integration. However, a major barrier identified was the lack of awareness among specialists regarding the potential benefits and applications of AI in ASD diagnosis. These findings underscore the need for targeted interventions, including strategic investment in training programs, infrastructure development, and awareness campaigns, to facilitate the seamless integration of AI into the ASD diagnostic landscape in KSA. By addressing these requirements and challenges, we can pave the way for more accurate, efficient, and timely ASD diagnosis, ultimately resulting in better results for families and people with ASD.
Indexed as
Identifiers
40627090What OpenQuestion holds
Registered trials
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.