“For most patients, X-ray is the first diagnostic imaging step on their path to a definitive diagnosis,” said Daan van Manen, General Manager for Diagnostic X-ray at Philips. “Radiology departments and their technologists are continually under pressure. With simpler and more efficient workflows we can reduce variability and staff workload, increase productivity, and enhance patient experience. Our partnership with Lunit to incorporate their diagnostic AI into our X-ray suite combines with a host of intelligent and streamlined workflow features in the Philips Radiography Unified User Interface (Eleva) across our digital radiography systems, enabling a smooth and efficient, patient-focused workflow. This is another step in contributing to providing a path to precision diagnosis.”
Lunit INSIGHT CXR chest detection suite accurately detects 10 of the most common findings in a chest X-ray, supports tuberculosis screening, and has shown clinical efficiency for detecting pneumonia, which can be an initial indication of COVID-19. By prioritizing cases with abnormality scores and facilitating fast triage of normal cases, the suite allows radiologists to focus on reading the abnormal cases.
“By partnering with Philips, a major player in diagnostic X-ray, our AI will be available to its significant global installed base,” said Brandon Suh, CEO of Lunit. “We look forward to collaborating together as we work towards our ambition to make data-driven medicine the new standard of care. Lunit will continue to build upon its current AI offering, making it better and better with time, and will continue to deliver best-in-class AI.”
Through breakthrough innovation and partnerships, Philips continues to integrate intelligence and automation into its Precision Diagnosis portfolio. This includes its smart diagnostic systems, integrated workflow solutions that can transform departmental operations, advanced informatics that can provide diagnostic confidence, and care pathway solutions that allow doctors to tailor treatment to the individual patient.