Automatic Hip Fracture Identification and Functional Classification with Deep Learning
This research aims to automatically identify hip fractures from hip radiographs using neural networks in order to prioritize radiologist’s reading queues and to provide early notification of important injuries to the emergency room and orthopedic physicians
Enhancing the Brain Tumor Center Database
The Brain Tumor Center Database is augmented by extracting key attributes (e.g. diagnosis Grade/Type, genetic markers and resection information) from the Electronic Medical Records system. These attributes exist only as elements in unstructured notes and currently are only accessible by painstaking manual review of patient records. The Information Commons provides a workflow to extract this data en masse using advanced Natural Language Processing techniques to ensure a high level accuracy. This will greatly reduce the time it takes to extract this data from the clinical record, and provide access to much more data than was previously accessible.