Rate My Professor David Dreizin

David Dreizin, MD, is a Professor in the Department of Diagnostic Radiology and Nuclear Medicine at the University of Maryland School of Medicine, University of Maryland, Baltimore. He earned a B.S. in Molecular Biology magna cum laude from Cornell University (1997-2001) and an M.D. from Weill Cornell Medical College (2003-2007). Dreizin completed a preliminary year in internal medicine at Albert Einstein College of Medicine/Montefiore Medical Center (2007-2008), diagnostic radiology residency where he served as chief resident at University of Miami/Jackson Memorial Hospital (2008-2012), and a fellowship in cross-sectional imaging at Johns Hopkins University (2012-2013). A Diplomate of the American Board of Radiology since 2012, he specializes in trauma and emergency radiology.

Dreizin's research interests include blunt and penetrating torso trauma, cervical spine trauma, pelvic trauma, quantitative imaging and volumetric analysis, and probabilistic modeling. On May 22, 2024, he founded the University of Maryland Trauma Radiology Artificial Intelligence Lab (TRAIL) to promote timely, accurate diagnosis for hemorrhage-related injuries in trauma victims using computer vision and machine learning. He has led numerous projects to detect and grade injuries, quantify injury severity, and predict clinical outcomes, with emphasis on explainable approaches and personalized precision diagnostics. His efforts are supported by an NIH R01 grant for human-centered CT-based CADx tools for traumatic torso hemorrhage (2023-2027) and the Radiological Society of North America R&E Foundation Scholar Grant (2016-2018). Key publications comprise 'Blunt polytrauma: evaluation with 64-section whole-body CT angiography' (Radiographics, 2012), 'Multidetector CT for penetrating torso trauma: state of the art' (Radiology, 2015), 'Multidetector CT of blunt cervical spine trauma in adults' (Radiographics, 2014), 'Penetrating Colorectal Injuries: Diagnostic Performance of Multidetector CT with Trajectography' (Radiology, 2016), 'Multidetector CT of mandibular fractures, reductions, and complications: a clinically relevant primer for the radiologist' (Radiographics, 2016), and 'Artificial intelligence CAD tools in trauma imaging: a scoping review' (Emergency Radiology, 2023).