The RSNA has launched its fourth annual artificial intelligence (AI) challenge, and this year's topic is pulmonary embolism (PE).
The RSNA partnered with the Society of Thoracic Radiology to create the massive dataset, which includes CT scans from five international research centers and detailed clinical annotations by more than 80 expert thoracic radiologists. The collection is the largest publicly available, expert-annotated pulmonary embolism CT data for AI, according to the RSNA.
The challenge is being run on a platform provided by Kaggle, and winners will receive $30,000, according to the society. Submissions are due October 26. The RSNA will announce the winners on November 23, with the top submissions receiving recognition during the virtual RSNA meeting the following week.
![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)
