The Radiological Society of North America (RSNA) will be holding a regional spotlight course on artificial intelligence (AI) on 23-24 September in Paris.
The two-day course, called Practical Applications of Artificial Intelligence, will focus on how radiologists can apply practical applications in AI to their everyday workflows and processes, according to the RSNA. It will also examine how AI will impact radiology's future. The program will be presented in English.
The course will be presented under the direction of Dr. Safwan Halabi from Stanford Children's Health, Dr. An Tang from the University of Montreal, and Dr. Marc Zins from Hôpital Paris Saint-Joseph.
Registration is now open on the RSNA's website.
![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)
