Imaging software developer Median Technologies is collaborating with Nice University Hospital in France to use artificial intelligence to identify imaging biomarkers for lung cancer screening.
The goal is to enhance diagnoses and provide physicians with new therapeutic decision-making tools based on medical imaging.
A key component is the French multicenter study on circulating tumor cells as a potential screening tool for lung cancer (AIR study), led by the Nice Hospital, in which more than 600 smokers or former smokers with chronic obstructive pulmonary disease are currently enrolled.
Median Technologies' role is to develop new algorithms to identify imaging biomarkers that indicate pulmonary nodule malignity.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
