Omar El Beggar
Papers
1
Total Citations
4
H-Index
1
About
Dr. Omar El Beggar is a leading researcher at the intersection of artificial intelligence, fuzzy logic, and medical diagnostics. His work focuses on developing transparent, explainable AI systems for critical healthcare applications, particularly in infectious disease detection. His most cited paper, "Design and development of a fuzzy explainable expert system for a diagnostic robot of COVID-19" (2023, 4 citations), pioneers a novel approach to creating rule-based diagnostic tools that are both accurate and interpretable. This work addresses a fundamental challenge in medical AI: ensuring that expert systems not only diagnose diseases but also provide clear, human-understandable explanations for their reasoning. By integrating fuzzy logic with explainable AI principles, Dr. El Beggar has advanced the field of intelligent medical robotics, making diagnostic systems more trustworthy and clinically useful. His research has significant implications for pandemic response and telemedicine, where transparent decision-making is essential. Dr. El Beggar’s contributions continue to shape how AI can be responsibly deployed in high-stakes medical environments, bridging the gap between machine learning performance and clinical interpretability.
Research Focus
Key Achievements
Top Papers
- 1