Perceptions of Special Education Professionals in the Kingdom of Saudi Arabia Regarding the Integration of Artificial Intelligence in Diagnosing Autism Spectrum Disorder.

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 th...

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Publicado en:Journal of Autism & Developmental Disorders p. 1
Autores principales: El-Ashram, Reda Ebrahim Mohamed, Aldaghmi, Ohud Abdulrahman, Mohammed, Sanaa Mostafa
Formato: Journal Article
Publicado: Springer Nature Jul2025
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Perceptions of Special Education Professionals in the Kingdom of Saudi Arabia Regarding the Integration of Artificial Intelligence in Diagnosing Autism Spectrum Disorder.
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          El-Ashram, Reda Ebrahim Mohamed
          Aldaghmi, Ohud Abdulrahman
          Mohammed, Sanaa Mostafa
        affil: Department of Business Administration, College of Business, Jouf University
      sug:
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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