Stewards of data and privacy, supporting radiologists throughout the state
Department experts participated in a nationwide effort to develop artificial intelligence (AI) technology that can accurately identify self-reported race through medical images. The research, which was published in The Lancet Digital Health, shows how AI can correctly predict a patient’s race—the race they identify with on hospital paperwork— with only the medical image, something a human radiologist would be unable to do.
technology in health care. Large stacks of clinical images forced digital solutions for data management and viewing, and this need led to the development of scheduling and metadata coexisting with the digital image data. Radiologists were some of the first users of computers in hospitals, driving network upgrades and new technologies like voice recognition. Informatics interventions started in the 1950s, with computer-aided diagnostic tools attempting image recognition tasks, and are now found in every aspect of a radiologist's workday.
Though radiology leads Imaging Informatics, it represents medical imaging throughout the enterprise. Imaging Informatics encompasses the life cycle of medical images, through acquisition and storage to processing and interpretation. The field develops the tools and methods to transform image data into information driving clinical decisions.
