The RSNA is launching a new AI certificate course designed especially for early career radiologists and trainees focused on implementing AI in emergency settings.
Some of the most mature radiology AI applications have been developed for use in emergency imaging, the RSNA said. The RSNA Emergency Imaging AI Certificate course is case-based and consists of six modules plus a fireside chat, and features expert instructors who will provide a deeper understanding of the steps involved in using AI algorithms in medical imaging, RSNA said.
The first module is available now. New modules will be released monthly through June 2024 and will be available on demand. Modules include brief didactic lectures and independent, hands-on exercises to help participants practice and apply what they learn.
Course directors are Marta Heilbrun, MD, of Intermountain Health in Salt Lake City, Utah; Po-Hao “Howard” Chen, MD, of Case Western Reserve University in Cleveland, Ohio; and Nina Kottler, MD, of Radiology Partners in Rancho Santa Fe, CA.
Enrollment information for all the RSNA Imaging AI Certificate courses can be found here.
![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.auntminnie.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)
