Identification of Abnormalities in Head Computerized Tomography Scans

摘要

Stroke and traumatic brain injuries are both leading causes of death and long-term disability globally. Early detection of abnormalities in head computerized tomography (CT) scans reduces patient risk of serious medical complications from brain injuries such as hemorrhagic stroke and cranial fractures. A machine learning algorithm trained to autonomously identify and classify head CT scan irregularities has the potential to decrease detection time of such anomalies and allow for quicker, more effective treatment.