Papers
4
Total Citations
806
H-Index
3
About
A. S. Albahri is a leading voice in trustworthy and explainable artificial intelligence (AI), with a particular focus on healthcare applications. Their work critically assesses the quality, bias risk, and data fusion challenges in AI systems, most notably in a landmark 2023 systematic review that has garnered over 666 citations, establishing it as a foundational reference in the field. Albahri’s research further explores the significance and requirements for risk-free trustworthy AI, addressing the tremendous potential and influence of algorithmic decision-making across sectors like education, business, and justice. In healthcare, they have advanced AI-based approaches for diagnosing and prioritizing autism spectrum disorder, contributing a systematic review that has already earned 60 citations. Their recent work extends to robotic hand control, integrating adversarial machine learning models with EEG sensor data fusion and fuzzy decision-making to enhance trust and explainability. Albahri’s contributions are pivotal in shaping the responsible deployment of AI, ensuring transparency and reliability in high-stakes environments.
Research Focus
Key Achievements
Top Papers
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