114: Radiology Partners’ approach to clinical AI applications: w/ Nina Kottler, MD, MS, FSIIM | Radiology Partners
Digital Pathology Podcast11/15/24 • 54 min
In this episode, I sit down with Dr. Nina Kottler, Associate Chief Medical Officer of Clinical AI at Radiology Partners, to dive into the evolving role of AI in radiology and how it can shape the future of digital pathology. Dr. Kottler shares her unique journey, expertise, and practical frameworks for implementing AI that enhance patient care and streamline diagnostic workflows.
Episode Highlights and Key Moments:
- [00:00:45] Introduction to Dr. Nina Kottler
Dr. Kottler discusses her background in applied mathematics, her journey into medicine, and her work at Radiology Partners, where she combines clinical practice with AI innovation. - [00:04:30] Breaking Down Complex Problems in AI
Nina explains her approach to tackling large clinical challenges by breaking them down into manageable parts, a method that’s essential for developing and optimizing AI solutions. - [00:08:15] The Role of Data Orchestration
We dig into “data orchestration” and how ensuring data is aligned with the right AI model is key to producing accurate and reliable clinical outcomes. - [00:11:45] Life Cycle of an Exam in Radiology
Nina takes us through each step in the radiology workflow—from the initial patient consultation to reporting—and highlights how AI can streamline and enhance each phase. - [00:17:00] Evolution of AI Models in Healthcare
We explore how AI has evolved, from early CAD systems to today’s multimodal and transformer models, and the exciting possibilities they bring to both radiology and pathology. - [00:23:20] Addressing the Lag in AI Adoption in Healthcare
We discuss the challenge of keeping up with AI advancements while balancing patient safety, regulatory standards, and the need for reliability in clinical settings. - [00:27:50] Frameworks for Reducing Variability and Improving Accuracy
Nina shares actionable frameworks that Radiology Partners uses to reduce variability and improve diagnostic precision—strategies that pathology can learn from. - [00:32:40] AI in Workflow Optimization: Where It Has Real Impact
We discuss specific use cases in clinical workflows that show where AI can bring the greatest value, especially in enhancing patient care through optimized processes. - [00:36:50] The Power of Multimodal AI and Vision-Language Models
Combining large language models with computer vision is moving diagnostics closer to comprehensive, AI-driven care—a promising development we explore in depth. - [00:42:15] The Future of Agents in AI
We dive into the concept of “agents” in AI and how these systems may soon coordinate multiple models for more complex and precise clinical analyses. - [00:48:10] Where to Learn More about Dr. Nina Kottler’s Work
Nina shares where you can catch her upcoming talks and presentations, plus resources for staying updated on the latest in AI for radiology and digital pathology.
If you're a pathologist, radiologist, or healthcare professional curious about AI’s impact on diagnostics, this episode is packed with practical guidance on integrating AI into clinical workflows. Join us as we explore how AI is shaping the future of radiology and pathology!
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11/15/24 • 54 min
Digital Pathology Podcast - 114: Radiology Partners’ approach to clinical AI applications: w/ Nina Kottler, MD, MS, FSIIM | Radiology Partners
Transcript
Breaking Down Large Problems
Nina: [00:00:00] It's too hard to take a very large problem and solve it on its own. The best way to solve a problem is to break it down into its individual components and look at the individual components and try to solve for that smaller piece and optimize to that which is the most important.
Best Practices in Healthcare AI
Nina: So we in healthcare have to figure out what are the best practices.
How do we make sure that AI is being cr
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