معرفی
Mena Shenouda is a Researcher in the Department of Radiology & Biomedical Imaging at Yale School of Medicine (Yale University). Their work focuses on advancing AI-driven medical imaging technologies to improve clinical outcomes, particularly in disease detection and diagnostic accuracy. Shenouda holds a Ph.D. in Medical Physics from the University of Chicago (2024) and a B.S. in Physics and Biophysics (Honors) from the University of Michigan (2019). They are also completing a Medical Physics Diagnostic Imaging Residency at Yale, set to conclude in 2026.
- Education:
- B.S. Physics, Biophysics (Honors), University of Michigan (2019)
- Ph.D. Medical Physics, University of Chicago (2024)
- Medical Physics Diagnostic Imaging Resident, Yale University (2026)
Research Interests: Shenouda specializes in applying artificial intelligence and deep learning to medical imaging challenges. Their work includes developing algorithms for detecting diseases such as COVID-19 and pleural mesothelioma, optimizing radiomics features for clinical decision-making, and improving image reconstruction techniques. They emphasize the generalizability and ethical implementation of AI models in healthcare.
Publications: Shenouda has authored peer-reviewed studies in high-impact journals like Journal of Medical Imaging and JCI Insight, focusing on deep learning applications in radiology and oncology. Their research bridges computational methods with clinical practice, addressing real-world challenges in imaging technology.
Professional Contributions: As part of the Radiology & Biomedical Imaging team, Shenouda collaborates on translational research initiatives. Their projects align with Yale’s broader goals in precision medicine and healthcare innovation.