Firefighters. Smokers. Former smokers. Veterans. Those age 55 and older. These are the people who can most benefit from lung screening. RadNet leverages AI and low-dose CT (LDCT) to revolutionize screening and help detect disease in an early stage, when it is most treatable.
Low-dose CT screening is the only exam currently proven to reduce lung cancer deaths.¹ If lung cancer is caught before it spreads, the likelihood of surviving 20 years or more improves to 81%.² RadNet optimizes its LDCT scans with technology from its AI subsidiary, DeepHealth. DeepHealth AI automates the detection and quantification of lund nodules on chest CT scans, enabling the radiologist to go further than naked-eye assessments. Clinicians can reduce the time-to-diagnosis and time-to-treatment—which can translate to better outcomes.
Deep Learning and Detection
Proper identification and diagnosis of detected lung nodules can be time-consuming, costly, and sometimes invasive. Deep learning has been shown to improve malignancy classification. The goal is to accelerate and expand the impact in clinical practice, bringing the highest-quality care to lung cancer patients.
RadNet's AI subsidiary, DeepHealth, has developed technology to assist radiologists with the time-consuming counting, measuring, and segmenting of lesions. It delivers:
- Automated volumetry for insights on the evolution of a nodule.
- No workflow change—no additional login or clicks.
- Support for detection, quantification, growth assessment, and classification.
- An average 40% reduction in reading time and higher reading agreement when using DeepHealth AI.
Florida Lung Health Coalition
RadNet is teaming with the Florida Lung Health Coalition to accelerate the uptake and adherence of lung disease screening in Florida. RadNet will leverage its state-of-the-art AI technology to help drive more accurate and early detection.
Want to learn more?
To learn more about RadNet’s AI solution for lung health screening, click here.