AI and Healthcare

What happens when artificial intelligence becomes a trusted partner in patient care? Healthcare leaders are increasingly exploring how AI can help clinicians make faster, more informed decisions while reducing administrative burden and improving patient outcomes. But deploying AI in medicine requires balancing innovation, trust, regulation, and clinical judgment. In this conversation, Dr. Scott Penberthy, Dr. Lindsey Cotton, and Dr. Doug Flora explore the future of cancer care, precision medicine, digital twins, physician adoption, implementation science, and the role of AI in supporting—not replacing—clinical decision-making. From cancer screening and treatment selection to workflow automation and predictive modeling, they discuss what healthcare may look like when every clinician has access to intelligence that helps them see what was previously invisible.

Cancer is often most treatable when it's found early—but what if we could detect it before symptoms ever appear? Advances in genomics, blood-based biomarkers, and artificial intelligence are giving researchers new ways to identify cancer earlier, understand disease at a deeper level, and move beyond one-size-fits-all treatment approaches. In this conversation, Dr. Scott Penberthy, Dr. Lindsey Cotton, and Dr. Doug Flora explore how emerging technologies are reshaping cancer detection, precision medicine, drug discovery, and clinical decision-making. They discuss the growing role of multimodal AI, the promise of next-generation sequencing, and why the future of healthcare may depend on finding patterns humans simply cannot see on their own. The goal isn't just better technology—it's earlier intervention, more personalized care, and better outcomes for patients.

Cancer treatment may be missing one of the body’s most important biological signals: circadian rhythm. In this conversation, sleep neurologist Dr. Anne Marie Morse explains how sleep timing, inflammation, immune function, and wearable data could fundamentally reshape cancer care. Emerging research suggests the timing of immunotherapy, chemotherapy, and even sleep disruption itself may influence treatment response, survival, and recurrence risk. The discussion explores chronotherapy, circadian genes, microbiome interactions, and how AI-driven analytics may help clinicians move beyond episodic care toward continuous, personalized monitoring.

AI is transforming healthcare at an unprecedented pace—but the biggest risks aren’t clinical, they’re legal, operational, and systemic. From data center infrastructure and environmental impact to reimbursement shifts and agentic AI workflows, the stakes are rising fast. New models from major tech players are poised to influence care delivery—and even get reimbursed based on outcomes—raising critical questions about ownership, liability, and control. Where does responsibility fall when AI drives decisions? How should hospitals evaluate vendors, data sources, and infrastructure risks? And what happens when automation outpaces regulation?

AI is making remarkable progress in healthcare — but translating that progress into real clinical impact is more complex than it seems. In this episode, we break down the State of Clinical AI in 2026, separating signal from noise and exploring what’s actually working today.