Why Radiology AI Needs Orchestration, Not More Algorithms with Jay Gurney and Franz Pfister

Scaling Radiology with AI: Kirill Lopatin on Solving the Capacity Crisis

In this episode of Scanning the Market, Jay Gurney is joined by Kirill Lopatin to explore the realities of AI adoption in radiology. They break down why most AI solutions fail to reach production, the true bottlenecks facing radiology practices, and why improving economics—not just accuracy—is key to success. Kirill shares insights on burnout, workforce shortages, and how “ready-to-sign” reporting could reshape workflows. The conversation also dives into the future of radiology, the risks of AI failure vs. over-reliance, and what practices must do today to stay competitive in a rapidly evolving market.

The Future of Radiology AI with Dr. Amine Korchi

In this episode of Scanning the Market, host Jay Gurney sits down with radiologist and healthcare innovator Amine Korchi to explore the evolving world of radiology AI.Amine shares his journey from clinical practice into the business and investment side of healthcare, offering a unique perspective on how AI is reshaping the industry. The conversation dives into why radiology became the focal point for AI in healthcare, the shift from point solutions to platforms, and what truly drives adoption in clinical settings.They also unpack the realities behind investment cycles, the challenges of implementing AI in hospitals, and why “slow” adoption may actually be right on time for healthcare. Looking ahead, Amine discusses the rise of multimodal AI, predictive diagnostics, and how radiologists’ roles will evolve in an AI-powered future.A must-listen for anyone interested in healthcare innovation, medical AI, and where the market is heading next.

How to Build a $1B Dollar AI Startup with AIDOC Chief Business Officer, Tom Valent

In this episode, Jay Gurney sits down with Tom Valent, Chief Commercial Officer at AIDOC, to explore what it really takes to build and scale AI in healthcare. From AIDOC’s early days as a single-algorithm startup to becoming a 500-person company powering over 100 million patient cases, Tom shares the behind-the-scenes realities of scaling clinical AI. They dive into the difference between FDA clearance and true production-grade AI, why infrastructure matters more than algorithms, and how AIDOC evolved into a full AI operating system for radiology. The conversation also covers foundation models, alert fatigue, AI-driven workflow transformation, commercialization challenges, IPO ambitions, and what the radiologist’s day could look like in three years. If you're building in healthcare AI — or trying to understand where the space is heading — this is one you won’t want to miss.

How to Navigate Hospital politics, workflow integration and breaking into the US Market with Thomas Bertinotti

In this episode, Jay sits down with Thomas Bertinotti from TheraPixel to unpack a decade-long journey building real-world AI for radiology. From breaking into the US market as a European startup, to navigating hospital politics, workflow integration, and product-market fit, Thomas shares what it actually takes to scale medical AI. They dive into foundation models, automation vs augmentation, why ROI matters more than hype, and the hard lessons learned from turning research into production-ready healthcare software. A must-listen for anyone building in AI, health tech, or enterprise software.

Why Radiology AI Needs Orchestration, Not More Algorithms with Jay Gurney and Franz Pfister

AI in radiology is moving fast, but not in the way most people think. More algorithms have not made hospitals smarter. They have made them more overwhelmed.In this episode, Jay Gurney sits down with Franz, co-founder of DeepC AI, to unpack why access to AI is no longer the problem and why fragmentation is. They explore how hospitals are drowning in disconnected tools, why deploying dozens of models creates new bottlenecks, and why the future is shifting from single-use algorithms to full AI orchestration.Franz explains the rise of foundation models, the reality of decentralised AI development inside hospitals, and how DeepC’s assistant Ada delivers real-time, context-aware intelligence directly into clinical workflows.If you want to understand where medical AI is actually heading and what it takes to make it work at scale, this episode is essential listening.