معرفی
Shadi Ebrahimian is affiliated with Yale School of Medicine's Radiology & Biomedical Imaging department. Their research focuses on AI-driven advancements in medical imaging, radiation safety protocols, and health equity in academic radiology. Key work includes developing AI algorithms for diagnostic quality control, optimizing CT radiation doses, and analyzing pulmonary embolism prognostics using CT features.
- Expertise: AI in Radiology, CT Imaging, Radiation Dosimetry, Medical Image Analysis
- Key Projects: Radiologist-trained AI models, national CT dose standards in Brazil, motion artifact detection
Research interests span AI integration into clinical workflows, improving diagnostic accuracy through machine learning, and addressing disparities in academic medicine. Recent studies explore predictive analytics for kidney stone composition and pulmonary embolism severity using CT radiomics.
Advising and grants: No formal students listed, but collaborates on multi-institutional studies across 4 continents. Active in global radiology initiatives addressing imaging quality and radiation safety in diverse clinical settings.
Labs/Teams: Part of Yale Radiology & Biomedical Imaging's AI and medical imaging research groups, contributing to interdisciplinary teams developing clinical AI solutions without data scientists.