From Interview #96
With Emily Lewis
In this information-packed interview, Emily Lewis shares a compelling vision for the future of AI in patient care. Drawing from her work in machine learning and generative AI, Lewis highlights how these tools are not just enhancing clinician efficiency but reshaping how patients engage with their own health. She explains how multimodal AI applications, from avatars to audio interfaces, can personalize communication based on learning preferences. Lewis emphasizes AI’s potential to foster equitable partnerships between patients and clinicians. The conversation also explores patient education, self-care, and the structural hurdles of deploying AI across institutions. With attention to AI for patient engagement and AI-driven personalized care, Lewis offers a deeply insightful look into the systems and safeguards necessary for responsible AI implementation.
From Interview #95
With Dr. Bernardo Perez-Villa
Dr. Bernardo Perez-Villa, Senior Innovations Engagement Partner at the Cleveland Clinic, shares grounded insights into the true drivers of successful innovation in healthcare. Drawing on his global background in biodesign and commercialization, he discusses the real-world challenges of bringing AI technologies from concept to clinic. From assessing unmet clinical needs to understanding payer dynamics and regulatory bottlenecks, Perez-Villa emphasizes frameworks that distinguish viable solutions from hype. Hosted by Dr. Sanjay Juneja, this conversation unpacks the realities of product-market fit, digital health business models, and how to responsibly scale innovation without compromising on patient safety or financial sustainability.
From Interview #94
With Emi Gal
How can artificial intelligence make full body MRI screening faster, more affordable, and more accurate? In this compelling interview, Ezra founder and CEO Emi Gal discusses how FDA-approved AI medical devices are transforming MRI scans into a powerful tool for early cancer detection. Gal outlines Ezra's three-tiered AI pipeline—enhancing image quality, assisting radiologists, and translating complex reports into plain language—to deliver a 22-minute, 9 full body MRI scan. Learn how this innovation is helping detect cancer in asymptomatic patients and why younger populations may benefit from early, proactive screening
From Interview #93
With Rajeev Ronanki
Rajeev Ronanki, CEO of Lyric, explores how the FDA’s evolving stance on artificial intelligence could reshape the future of drug development and healthcare delivery. In this compelling exchange, he unpacks the promise of Elsa—a tech-forward initiative by the FDA—and why it signals a paradigm shift from bureaucratic bottlenecks to data-driven decisions. Rajeev emphasizes how AI can accelerate therapeutic innovation, reduce inefficiencies, and make regulatory processes more transparent and predictive. His insights speak directly to healthcare executives, clinicians, and digital health innovators eager to understand federal AI adoption and its implications for clinical practice and pharma R&D.
From Interview #92
With Dr. Colleen Lyons
In this in-depth conversation, Dr. Colleen Lyons dives into the nuanced intersection of ethics and AI in healthcare, spotlighting overlooked risks and opportunities in today’s clinical AI tools. Drawing from her background at the FDA and in academia, she critiques the hollow nature of many ethical AI frameworks and calls for transparency and value-based governance over check-the-box compliance. The conversation covers the Belmont Report’s enduring relevance, AI's impact on autonomy and informed consent, and the systemic bias embedded in data. With regulatory landscapes still fragmented, Lyons argues for proactive, values-driven leadership to ensure AI adoption benefits patient care without unintended harms—particularly in vulnerable populations. If you're working at the frontline of AI implementation in provider systems or clinical operations, this episode is essential listening.
From Interview #91
With Dr. Spencer Dorn
In this in-depth conversation, Dr. Spencer Dorn, Vice Chair and Professor of Medicine at the University of North Carolina, explores the evolving role of AI scribes in healthcare. He examines their ability to reduce clinician burnout, improve patient experience, and integrate into EHR systems. Dr. Dorn discusses both the potential for clinical decision support and the limitations of current AI scribe technology, including contextual awareness, coding accuracy, and ROI considerations. He also reflects on broader AI risks, from critical thinking erosion to the impact on patient-clinician relationships, offering a nuanced roadmap for responsible adoption.
From Interview #90
With Adrian Mendes
Adrian Mendes, CEO of Perimeter Medical Imaging, discusses how AI-powered imaging is transforming breast cancer surgery. Leveraging optical coherence tomography (OCT) combined with AI, surgeons can visualize tumor margins at microscopic levels in real-time, reducing the need for repeat surgeries. This innovation offers higher precision in tissue removal, preserving healthy tissue while ensuring complete cancer excision. Mendes also addresses broader applications in head and neck cancers and the role of high-quality data in advancing AI models. The conversation highlights economic benefits, patient psychological relief, and improved access to high-quality surgical outcomes in both urban and rural healthcare settings.
From Interview #89
With Dr. Harvey Castro
Hematologist-oncologist host Dr. Sanjay Juneja sits down with emergency physician and AI advisor Dr. Harvey Castro to demystify agentic AI in healthcare. Castro explains how clinician and patient digital twins could safely scale expertise, reduce ER bottlenecks, and improve decisions when paired with human oversight. The discussion compares build-versus-buy choices for ambient scribing and other use cases, notes when open-source models can lower costs, and outlines how federated learning lets hospitals benefit from broader data without exposing PHI. They also tackle workforce shortages, forecasting near-term wins from ambient documentation, monitoring at home, and culturally aware guidance at the bedside. Throughout, Castro stresses pragmatic guardrails—HIPAA, FDA pathways, and clinician validation—to mitigate hallucinations and bias. For leaders planning an AI strategy, the conversation offers a clear, reader-first roadmap that highlights ai agents in healthcare while staying focused on patient outcomes.
From Interview #88
With Dr. David Fajgenbaum
In this insightful interview, Dr. David Fajgenbaum, Co-founder of Every Cure, shares how artificial intelligence is revolutionizing rare disease research and treatment. Drawing from his own groundbreaking work in drug repurposing and precision medicine, Dr. Fajgenbaum explains how AI tools can rapidly identify therapeutic opportunities hidden in existing medical data. He discusses the challenges of rare disease diagnosis, the importance of cross-disease data analysis, and the potential of AI to accelerate life-saving discoveries. Through a mix of personal experience and scientific expertise, he paints a compelling vision for how AI could reshape the landscape of rare disease care and improve patient outcomes worldwide.
From Interview #87
With Rajiv Haravu
In this in-depth interview, Rajiv Haravu, SVP of Product Management at IMO Health, explores the complexities of healthcare data normalization and its vital role in improving data quality across clinical systems. Haravu outlines the challenges of variability in documentation, from lab results to unstructured physician notes, and shares how IMO’s Precision Normalize and Precision Sets products address these issues. He discusses the interplay between structured and unstructured data, the role of terminology management, and the importance of adapting to evolving definitions. With insights on AI and natural language processing, Haravu reveals how IMO is integrating advanced tools while maintaining precision in clinical coding—empowering healthcare organizations to unlock the full potential of their data.
From Interview #86
With Dr. Euan Ashley
In this full interview, Dr. Euan Ashley, Chair of the Department of Medicine at Stanford, shares how preventive cardiology is being transformed by remote monitoring, AI, and wearable technologies. Ashley highlights how early detection through wearable devices can identify subtle changes in cardiac function before symptoms appear, enabling timely interventions that prevent severe events. He discusses advances in remote cardiac monitoring, AI-powered risk prediction, and how continuous data streams are improving both individualized care and population health. This conversation offers a compelling vision for integrating cutting-edge technology into preventive cardiovascular medicine.
From Interview #85
With Jason Alan Snyder
In this full interview, Jason Alan Snyder, Futurologist, Inventor, and Technologist, explores the urgent issues of AI in healthcare data, from privacy and ethics to ownership and monetization. Snyder highlights how digital twins—virtual representations of individuals built from lab results, biometrics, genomes, and behaviors—are being used without consent or compensation. He warns of the dangers of poor data quality, decay, and fragmentation, which lead to flawed AI-driven medical decisions. Snyder envisions a future where individuals own and control their health data, benefiting from AI’s potential while avoiding exploitation. The conversation offers a roadmap for building ethical, transparent, and patient-centered AI systems in healthcare.
From Interview #84
With Dr. Alister Martin
In this full interview, Dr. Alister Martin, CEO of A Healthier Democracy and Assistant Professor at Harvard Medical School, shares a powerful vision for how AI can both lower healthcare costs and expand access for underserved communities. Martin discusses the concept of 'money as medicine,' showing how targeted financial investments in social determinants of health can prevent costly emergency care. He explores AI's role in identifying high-need patients, optimizing care coordination, and connecting people to the right resources before medical crises occur. This conversation blends clinical insight with public health strategy, offering actionable ideas for leaders seeking to align cost savings with better health outcomes.
From Interview #83
With Pelu Tran
In this full interview, Pelu Tran, CEO of Ferrum Health, explores the complex realities of AI governance in healthcare and how hospitals can navigate the tension between innovation, security, and regulatory compliance. Tran discusses the technical, clinical, and business barriers to AI adoption, from vendor-cloud mistrust to the high costs of deploying and maintaining AI solutions. He explains why governance platforms are essential for ensuring AI models perform safely across diverse patient populations, and how middleware infrastructure can help hospitals integrate and manage AI at scale. This conversation offers actionable insights for leaders facing AI adoption bottlenecks.
From Interview #82
With David Norris
In this full interview, David Norris, Co-Founder and CEO at Affineon Health, shares how AI is revolutionizing healthcare administration by reducing the overwhelming burden of lab result management, documentation, and communication. Norris discusses how AI agents can triage clinical inboxes, prioritize urgent results, and even engage patients directly, allowing providers to focus on meaningful patient care rather than administrative overload. He highlights the impact on burnout reduction, the potential for preventive interventions, and how AI tools can level up both physicians and advanced practice providers by surfacing actionable insights from vast longitudinal data. This conversation offers practical solutions for integrating AI into healthcare workflows.
From Interview #81
With Krish Ramadurai
In this in-depth interview, Krish Ramadurai, Partner at AIX Ventures, shares his perspective on what's real and what's overhyped in AI development in healthcare. He explains the importance of domain expertise, the role of clinical workflow automation, and why business models must align with enterprise value creation. Ramadurai also discusses AI’s role in drug development, the challenge of regulatory compliance, and the strategic investments that drive sustainable innovation. His insights provide a roadmap for healthcare leaders navigating AI investment opportunities.
From Interview #80
With Dr. Azra Raza
Dr. Azra Raza, Professor of Medicine at Columbia University, challenges the cancer research community to shift focus from treating late-stage disease to detecting cancer at the 'first cell' stage. Drawing on decades of clinical work and a unique repository of 60,000 patient samples, she outlines how AI-powered, continuous monitoring could revolutionize early detection. Dr. Raza critiques the limitations of current models and screening methods, advocating for human-based research and proactive monitoring to prevent cancer before it requires invasive treatment. Her vision combines multi-omics analysis with implantable biosensors to identify biomarkers long before cancer reaches stage one, aiming to reduce suffering and improve outcomes.
From Interview #79
With Dr. Nigam Shah
Dr. Nigam Shah, Co-Founder of Atropos Health and Chief Data Scientist at Stanford Health Care, explores how AI implementation in healthcare must shift from experimental models to scalable, sustainable solutions. Drawing on analogies from automotive safety, Dr. Shah emphasizes creating ecosystems for local validation, continuous monitoring, and defining clear context for use. He discusses how AI can increase healthcare access, avoid the 'Turing trap' of replacing humans for tasks they already do, and instead focus on reducing unnecessary visits and expanding provider capacity. With insights into AI healthcare data usage and frameworks for responsible AI lifecycle management, this conversation offers a roadmap for healthcare leaders to deploy AI effectively.
From Interview #78
With Bob Battista
In this wide-ranging interview, Bob Battista explains how AI can speed drug repurposing—if data can flow across today’s regulatory and commercial silos. He points to untapped knowledge inside pharmaceutical call centers, patient-reported outcomes, and physician off‑label use that rarely reaches researchers. Battista argues that safe-harbor policies for pharmaceutical data sharing would unlock thousands of potential indications hiding in plain sight, while AI organizes mechanistic and clinical evidence for decision makers. The conversation also explores living clinical guidelines, earlier diagnostic staging, and the economics that slow evidence adoption. For healthcare leaders, the message is clear: pair modern analytics with governance reform to expand access, improve outcomes, and strengthen patient empowerment in healthcare.
From Interview #77
With Tom Neyarapally
In this full interview, Tom Neyarapally, CEO and Co-Founder of Archetype Therapeutics, discusses the transformative role of AI in drug development. He explores how generative AI is accelerating drug discovery, enabling drug repurposing, and reshaping therapeutic innovation. Neyarapally provides a forward-looking perspective on the future of AI in healthcare, drawing from his deep expertise and hands-on leadership in the biotech industry.
From Interview #76
With Dr. Debra Patt
In this in-depth interview, Dr. Debra Patt, Executive Vice President of Texas Oncology and Chair of ASCO’s Artificial Intelligence Task Force, shares her insights on how AI is revolutionizing cancer care. She discusses real-world applications, from AI-enhanced diagnostics to ambient AI for reducing physician burnout, and explores how AI can improve patient outcomes, streamline administrative tasks, and reduce healthcare costs. Dr. Patt also highlights the promise of AI in drug discovery, clinical trial design, and personalized medicine.