AI Augmented Radiology

We will use AI technologies to improve the acquisition, analysis, and clinical use of radiological imaging. Our team is at the forefront of translational biomedical imaging research, and our highly cited works have appeared in Nature Medicine, PLOS Medicine, Radiology, and Radiology: Artificial Intelligence. We aim to combine our domain expertise as practicing clinicians with our technical expertise as computer scientists to discover novel ways of obtaining and utilizing imaging in the 21st Century.

AI Augmented Pathology

Leveraging the largest repository of stimulated Raman histology data, a technique pioneered by Dr. Daniel Orringer, we will develop rapid, AI-based methods for predicting key mutations and histopathological features in tumors. These tools will enable better and more accurate intraoperative diagnosis enabling tailored surgical decision-making and personalized clinical trial stratification. 

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