Dr. Rachael Callcut, Associate Professor of Surgery at the University of California, San Francisco (UCSF) Medical Center and Director of Data Science for the Center for Digital Health Innovation, partnered with her radiology colleagues and GE Healthcare to create an initial algorithm that can detect pneumothorax, a condition which strikes nearly 74,000 Americans each year[1] and can be deadly if not diagnosed quickly and accurately.[2] The challenge: a patient with this condition could wait between two to eight hours for his or her X-Ray to be read.[3]
Today, Dr. Callcut and the UCSF team’s use case and data science approach has become a suite of algorithms, known as Critical Care Suite* on the mobile Optima XR240amx X-Ray system, powered by the Edison platform, that can alert the clinical team of potential pneumothorax cases as soon as the patients are scanned, so they can prioritize reading them.