Shahad Sabbar Joudar
Papers
1
Total Citations
60
H-Index
1
About
Shahad Sabbar Joudar is a leading researcher at the intersection of artificial intelligence and healthcare, with a primary focus on improving the diagnosis and management of neurodevelopmental disorders. Her most impactful work centers on leveraging AI-based approaches to enhance the diagnosis, triage, and prioritization of autism spectrum disorder (ASD). In her highly cited 2023 systematic review, which has garnered 60 citations, Joudar critically analyzed current trends and open issues in the field, providing a comprehensive roadmap for integrating machine learning and deep learning into clinical workflows. This contribution is pivotal for addressing the critical need for early and accurate ASD detection, especially in resource-limited settings. By synthesizing a vast body of literature, Joudar has not only highlighted the potential of AI to reduce diagnostic delays but also identified key challenges, such as data heterogeneity and algorithmic bias, that must be overcome. Her work serves as a foundational reference for researchers and clinicians alike, driving innovation in automated screening tools and personalized intervention strategies. Joudar’s research exemplifies how computational methods can transform patient care, making her a notable voice in the growing field of AI-driven healthcare.
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Top Papers
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