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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Digital accessibility in the era of artificial intelligence-Bibliometric analysis and systematic review
Khansa Chemnad1, Achraf Othman1
1Mada Qatar Assistive Technology Center, Doha, Qatar.
Introduction:
Digital accessibility involves designing digital systems and services to enable access for individuals, including those with disabilities, including visual, auditory, motor, or cognitive impairments. Artificial intelligence (AI) has the potential to enhance accessibility for people with disabilities and improve their overall quality of life.
Methods:
This systematic review, covering academic articles from 2018 to 2023, focuses on AI applications for digital accessibility. Initially, 3,706 articles were screened from five scholarly databases-ACM Digital Library, IEEE Xplore, ScienceDirect, Scopus, and Springer.
Results:
The analysis narrowed down to 43 articles, presenting a classification framework based on applications, challenges, AI methodologies, and accessibility standards.
Discussion:
This research emphasizes the predominant focus on AI-driven digital accessibility for visual impairments, revealing a critical gap in addressing speech and hearing impairments, autism spectrum disorder, neurological disorders, and motor impairments. This highlights the need for a more balanced research distribution to ensure equitable support for all communities with disabilities. The study also pointed out a lack of adherence to accessibility standards in existing systems, stressing the urgency for a fundamental shift in designing solutions for people with disabilities. Overall, this research underscores the vital role of accessible AI in preventing exclusion and discrimination, urging a comprehensive approach to digital accessibility to cater to diverse disability needs.
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