Rad AI

And that’s a wrap! Now that #RSNA25 has come to a close, we’re reflecting on the conversations and topics that stood out: 1️⃣ Radiologists’ shift in mindset: augmentation, not replacement The fear of “AI replacing radiologists” felt noticeably lower this year. Instead, radiologists talked about AI as a way to reduce cognitive load, stay focused on complex cases, or spend more time on the work that matters most to them. 2️⃣ Openness to AI across the workflow From triage to automatic clinical-history gathering to reporting, radiologists are receptive to AI as long as they maintain agency and the technology clearly improves daily work. 3️⃣ Governance, safety, and scale moved into the spotlight There have always been questions about deployment expectations, but this year solution monitoring and governance across sites was discussed just as much. 4️⃣ Synthetic data as an enabler and a risk Synthetic data drew significant attention as a way to accelerate model development and strengthen limited datasets, while also raising valid concerns around bias. If there was one throughline this year, it’s that the expectations of what AI needs to deliver from day one are crystallizing. What was your main takeaway from RSNA this year? Share it in the comments!

Rad AI was recently featured in Modern Healthcare’s roundup, “The devices and AI tools making waves at RSNA 2025,” alongside Philips, GE HealthCare, Siemens Healthineers, Samsung Healthcare, and more. Read the full roundup – featuring our latest speech recognition technology – here: https://hubs.ly/Q03WZX5d0

What a night! ✨ Thank you to everyone who joined our "Come Together" event on Tuesday. After a full day at Radiological Society of North America (RSNA), it was the perfect reset to relax, connect and share some laughs (and a photo booth) with the people who make this community what it is. We hope you had as much fun as we did! Matt Bressers Phillip G. Ivan Vinueza, MBA, MSDS David Ross, MBA Anastasia Bass B.J. Crowell Carson White Roxanne Mennella Joseph Mack Reed Humphrey Joseph Guiffrida Jeff Chang

As Imaging Technology News (ITN) reported, our next-generation speech recognition is designed not just to transcribe but to transform reporting efficiency. They highlighted how “by integrating workflow analytics, Rad AI's reporting engine goes beyond speech recognition" to address dictation redundancy. This enables an intelligent feedback loop that supports our "speak less, say more" philosophy to help improve both the quality and efficiency of radiology reports. Read the full article here: https://hubs.la/Q03WW78c0

As another RSNA comes to a close, we offer our sincere appreciation to every person who stopped by the booth or attended our event. Whether it was a demo, a question, or to say "hi," every conversation and piece of feedback helps us build solutions for radiology and reminds us why we are proud to be a part of this community. If we didn’t get to meet in person, we’d still love to connect after RSNA. Connect with us here: https://hubs.la/Q03WLhW70

“There’s a difference between efficiency and habit.” Demetri Giannikopoulos, our Chief Innovation Officer, sat down with The Medical Innovation Podcast where he discussed why radiologists are turning to Rad AI for real workflow change and the impact of our collaboration with Radiological Society of North America (RSNA) Ventures. Find the full episode on Spotify or Apple: Spotify: https://hubs.la/Q03WKgDq0 Apple: https://hubs.la/Q03WKkGL0

Why are radiologists facing a critical storm? Rising case volumes, reporting complexity, and an explosion of medical knowledge that doubles roughly every 72 days. In today’s workload, even a few minutes spent looking for the right insight adds real strain to an already high-stress environment. Imagine Radiological Society of North America (RSNA)'s extensive peer-reviewed expertise exactly when a radiologist needs it. That’s what Rad AI is doing by integrating RSNA’s trusted knowledge directly into the reporting workflow, surfacing differentials and evidence-based insights automatically with no added steps. At the AI Theater, Rishi Seth MD CIIP, shared the broader vision: how this work sits within Rad AI’s Agentic AI framework, where the solution does more than recognize context and begins to take action on it, like synthesizing patient history, integrating evidence-based guidance, and automating comparisons like RECIST and volumetrics. The goal is simple: reduce friction, surface what matters instantly, and give radiologists the information they need before they have to go searching for it. If you missed the session, today’s your last chance to stop by Booth #4753.

As workloads rise and expectations for speed and accuracy continue to grow, even minor reporting inefficiencies become noticeably amplified across a full day of reads. This week, AuntMinnie.com covered our next-generation speech recognition technology, noting that it “understands clinical context, recognizes uniqueness, and adapts to individual radiologists” while accurately handling diverse accents, overlapping speech, and complex medical terminology. If you’re at #RSNA25, we’d love to share more about what this means in practice. Visit us at Booth #4753 tomorrow to learn more. Read the full article here: https://hubs.la/Q03Wzcyz0

Don’t miss it! Our RSNA Ventures deep dive starts in 20 minutes at the AI Theater (4:30–4:50 PM CT). Many radiologists have been asking about this, and we’re excited to share more!

“Today, radiologists are limited by reporting tools that simply transcribe words but don’t understand the user behind them – still missing subtleties, struggling with clinical terminology, and forcing radiologists to spend valuable time correcting basic errors. We built this technology to understand context so that radiologists can return focus to diagnosis, not documentation”, said Doktor Gurson, CEO at Rad AI, in a recent Newsweek article. Rad AI’s new multi-model architecture addresses challenges like diverse accents, overlapping speech, and the complexity of medical terminology by combining multiple speech engines powered by Rad AI’s proprietary modeling and a unique “voting” algorithm that determines the most accurate understanding in real-time. If you’re at RSNA, visit Booth #4753 to learn more! Read the full article here: https://hubs.la/Q03WsqtJ0