Medical imaging is the foundation of modern diagnosis. But as AI reshapes what scanners can see and what clinicians can do, the gap between technological progress and real-world delivery has never been more visible.
In this episode of The Futurist, host Ian Khan sits down with leading voices at the intersection of technology and care delivery to find out where that gap stands today.
Shez Partovi, MD, Chief Innovation Officer at Philips, shares data from the company's annual Future Health Index, revealing that 66% of physicians are experiencing burnout, but that AI has the potential to alleviate their burden and bring the joy back into medicine. He also shares how Philips' AI-powered imaging is making a big difference now.
The shift isn't coming. It's already here.
Gretchen Brown, Chief Nursing Information Officer at Stanford Health Care, brings a 30-year clinical perspective on what it will take to shift the culture around AI adoption.
Mike Mosquito, Head of Enterprise Automation and Integration at FOX Rehabilitation, makes the case for why data is the new currency of healthcare operations.
Atul Gupta, MD, Chief Medical Officer, Diagnosis and Treatment, Philips, details how AI is creating real-world superpowers to diagnose and treat faster than ever before, even giving the power to predict and prevent disease.
Carlos Cordon-Cardo, MD, Chairman of Pathology at Mount Sinai, explains how digital pathology is turning cancer grading from a subjective judgment into an objective, reproducible science.
A candid conversation on where AI is working, where it isn't, and what comes next.
Key Highlights from the Session
How diagnostic imaging informs nearly 80% of clinical decisions, and why AI is now central to managing that load
The three ways AI is helping advance healthcare in a health system through automation, augmentation, and agility while humans monitor for adverse events
Why AI is critical for radiology and how it’s making its way into the workflow to deliver better care for more people
How digital pathology is turning cancer grading from a subjective call into an objective, reproducible science
Why AI will not replace radiologists and clinicians, and what will actually change about how they work
