RSNAI Monthly—October 2025 

The Radiological Society of North America (RSNA) leads the charge in advancing artificial intelligence (AI) as a tool to drive excellence in patient care and health care delivery. RSNAI Monthly is a collection of media briefs to help news outlets stay abreast of RSNA’s latest AI initiatives.

Technical Exhibits at RSNA 2025 Feature Largest-Ever AI Showcase
With 228 exhibitors demonstrating AI and machine learning tools and 111 companies registered to exhibit in the AI Showcase, Technical Exhibits at RSNA 2025 will provide the premier forum to see the most promising applications in medical imaging AI. Attendees can interact with products, watch hands-on demonstrations in the AI Theater and explore practical clinical uses for AI in radiology practice. The Showcase will also house RSNA-led initiatives and research to streamline radiology workflows and improve patient care. 

RSNA Enters First-of-Its-Kind Partnership with Rad AI
In October, RSNA launched RSNA Ventures, a mission-aligned subsidiary of the Radiological Society of North America (RSNA), and announced a strategic partnership with Rad AI, a leader in generative AI for healthcare, to advance innovation in radiology and imaging technologies. The collaboration marks a pivotal step toward its commitment to developing and commercializing solutions that enhance the practice of radiology, improve patient care and drive the future of medical imaging. By joining forces with Rad AI, RSNA Ventures aims to bring trusted, RSNA-powered innovations to market with speed and impact.

Barcelona RSNA AI Spotlight Course Draws Attendees from 21 Countries

The October 16 – 17 course “Radiology Reimagined: Advancing Clinical Practice Through AI Innovation” drew 70 attendees representing 21 countries to learn real-world applications from global experts in radiology AI. Participants gathered in Barcelona to gain a deeper understanding of the AI evaluation and deployment lifecycle and examined the role of generative AI in medical imaging practice. Didactic sessions, case-based learning and interactive discussions prepared attendees to lead evidence-based AI implementation and champion innovations that improve both patient outcomes and professional practice. 

RSNA Journals Highlight AI’s Role in Radiology Research and Practice
In its October issue, RSNA’s flagship journal Radiology published original research, expert reviews and commentary that encompasses the newest developments in AI, including a deep learning model for breast cancer risk prediction, a primer for AI in radiology, and the promise of deep learning for reducing false alarms in lung cancer screening. 

RSNA’s journal Radiology: Artificial Intelligence published a multi-society–recommended syllabus for teaching AI in radiology applications as well as commentary on the breadth of training data needed for AI models, the feasibility and challenges of privacy-preserving deep learning in medical imaging, how AI could transform Alzheimer’s disease diagnosis and the emergence of generalist AI in medical image segmentation. 

Original research in Radiology: Cardiothoracic Imaging explored AI’s impact on reader agreement in interpreting coronary CT angiography and an open-source model that uses chest radiographs to predict respiratory mortality from COPD, while a Radiology Advances study found that AI can also use chest radiographs to measure body composition. 

With its suite of six premier journals, RSNA covers the breadth of groundbreaking research, career-advancing education, and specialty-focused techniques and trends for medical imaging professionals.

RSNA Aneurysm AI Challenge Concludes with 16,298 Submissions
More than 1,400 participants entered the RSNA Intracranial Aneurysm Detection AI Challenge, which concluded in October with 16,298 submissions from 77 countries. Developers were invited to create open-source machine learning models to detect and precisely locate intracranial aneurysms across various types of medical images. The Challenge provided expert-curated anonymized datasets from thousands of real clinical cases representing a variety of modalities, including CT angiography, MR angiography, T1 post-contrast MRI and T2-weighted MRI.

Winning teams will be recognized in the AI Theater during RSNA’s 111th Scientific Assembly and Annual Meeting (RSNA 2025), held Nov. 30 – Dec. 4 at McCormick Place in Chicago. The validated open-source models will pave the way for automated solutions to accurately and efficiently diagnose brain aneurysms across a wide range of brain imaging, which will ultimately save lives by enabling earlier intervention—before a catastrophic aneurysm rupture.

1,670+ Professionals Enrolled in RSNA Imaging AI Certificate Courses
More than 1,670 medical imaging professionals have enrolled in RSNA’s Imaging AI Certificate Program, which offers on-demand training that blends a case-based curriculum with practical applications in four course tracks. Participants can earn a Foundational Certificate, Advanced Certificate, Emergency Certificate or Chest Certificate to improve knowledge and skills in medical imaging AI. The program is open to radiology professionals at any career stage, and RSNA offers both individual enrollment and resident group enrollment.

MIDRC Seminar Open to Medical Community
The Medical Imaging Data Resource Center (MIDRC), funded by the National Institute of Biomedical Imaging and hosted at the University of Chicago, is co-led by RSNA, the American College of Radiology, and the American Association of Physicists in Medicine. Held on the third Tuesday of the month, the Seminar Series is an opportunity for members of the medical community at large to hear directly from the MIDRC team. The next session, planned for Tuesday, Nov. 18, from 2:00 to 3:00 p.m. CT, will feature research presentations from MIDRC investigators on new and noteworthy advances, and includes a live Q & A session for all attendees. Free registration is required.