Using AI to aid Radiologists

Our flagship solution, VisiRad™XR, uses sophisticated computer vision technology to identify lung nodules and masses in chest x-rays. VisiRad, the cornerstone to our mission of improving lung cancer outcomes, is modeled after the expert accuracy and acumen of world-class radiologists practicing at the top of their license.

Identifying overlooked lung nodules is an opportunity to stage-shift lung cancer and treat patients sooner

Early detection is the key to improving outcomes for cancer patients. Currently, 49% of lung cancer diagnoses occur at Stage IV, where the cancer has metastasized to other organs and the prognosis is often grim—the 5-year survival rate for stage IV lung cancer is only 10%. Lung cancer is generally asymptomatic until late stages and is often only detected incidentally, when a chest x-ray or CT is performed for another reason.

Lung nodules, an early indication of lung cancer, can be detected in chest x-rays; however they are often overlooked due to their visual subtlety and rarity in routine care. Combined with increasingly intense workloads for radiologists (over 240 million x-rays are performed per year in the US), the opportunity to aid clinicians in identifying lung nodules is ever-growing. VisiRad aims to close the gap in current early lung cancer detection, enabling hospitals to treat cancer patients sooner when outcomes are much better.

VisiRad™ puts overlooked findings in plain view

Our Model Is Different

What makes VisiRad different? Our model is based on a growing contributory database consortium using longitudinal outcomes. Combined with our computer vision technology and advanced machine learning, this more accurate data will lead to a new standard of care based on superior diagnostic accuracy.

VisiRad is available to hospitals, radiology practices, nodule clinics, and health systems for research purposes only.

 Sign up for a complimentary VisiRad demo*

  • This field is for validation purposes and should be left unchanged.

*For research purposes only. Click here for more information on participation, privacy and security.