VIENNA – It's radiology's equivalent of the Ryder Cup in golf: Is Europe or the U.S. leading the way? We put this and other tricky AI-related questions to Rick Abramson, MD, ECR 2024 plenary lecturer and chief medical officer of Annalise.ai.
Ahead of Thursday's keynote lecture -- Radiology, AI, and the Analog-Digital Frontier -- he also elaborates on the current state of the sector and the latest market trends. Coming from Nashville, Tennessee, he also shares his thoughts on country music.
For more coverage from ECR 2024, please visit our RADCast.
Video produced by Christof.G.Pelz | GRAFIFANT Creation | www.grafifant.at | 2024
![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)
