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Dr. Bridge

Christopher Bridge, PhD

Dr. Bridge

Christopher Bridge, PhD


Massachusetts General Hospital


MGH Research Fellows



For nearly 30 years, the funding provided by the Rappaport Foundation to physicians and researchers has allowed brilliance to flourish and breakthroughs to triumph in the areas of neurologic diseases and mental illness.

Chris has a background in computer engineering and artificial intelligence (AI), which he studied as an undergraduate student in Engineering at the University of Cambridge and a doctoral student at the University of Oxford. He received his DPhil in 2017 for his work on the application of machine learning techniques to the analysis of fetal cardiac ultrasound videos. In 2017, he joined the MGB Data Science Office (DSO) where he has worked on industry collaborations to create commercializable AI models across a wide variety of applications in clinical medicine, including trauma, urology, population health, and neurology with a particular focus on stroke care, and spinal stenosis detection. Working with a multidisciplinary team of collaborators, he developed a suite of AI models for stroke detection and quantification from contrast and non-contrast CT, and diffusion weighted MRI, one of which was recently given FDA breakthrough device status to accelerate the regulatory process. Through his work with the DSO, he has lead the deployment of several AI models for validation on live patient data within the hospital system in a drive towards translation of MGB’s cutting edge research into practice, and has developed a particular interest in standards-based communication of AI results across medical disciplines. In addition to his work with the DSO, Chris joined the Martinos Center in 2020 working in the Quantitative Translation Imaging in Medicine Laboratory, and became an Instructor in Radiology in 2021. His work currently focuses on quantification of uncertainty within brain tumor delineation, improvements to the FreeSurfer neuroimaging suite, and methods development within radiology-based AI.