Highlights of our conversation include:

• Data orchestration: Nina shares how aligning data with the right AI models ensures high-quality results, emphasizing the complexity of this process in clinical applications.
• Life cycle of an exam: A breakdown of each step in radiology workflows, from ordering imaging to report generation, and how AI can streamline each phase.
• Reducing variability and improving diagnostic accuracy: We discuss actionable AI frameworks that radiology has adopted and that pathology can learn from to enhance precision and reduce inconsistencies.
• Evolving AI models in healthcare: A look at how AI has progressed from rule-based CAD systems to sophisticated large language and multimodal models and how these advancements are applied in clinical settings.

For those in radiology, pathology, or anyone curious about AI’s real-world application in healthcare, this episode offers a rare, expert view on AI integration and innovation that’s both practical and forward-thinking. Join us as we discuss data orchestration, breaking down complex workflows, and the exciting ways AI is enhancing precision and efficiency in digital diagnostics.

I hope you enjoy this episode as much as I enjoyed recording it. Dive in, and let’s explore the future of AI in radiology and pathology together!