AI and Healthcare

Healthcare systems face a critical question: build custom AI tools tailored to their workflows, or buy ready-made solutions? This video unpacks the operational, financial, and clinical factors that inform that decision, including insights on cost, customization, integration, and innovation in patient-centered AI. Dr. Sanjay Juneja (https://sjunejamd.com/) interviews Dr. Harvey Castro (https://www.linkedin.com/in/harveycastromd/) to explore the nuances of AI adoption in hospital systems. They break down the value of federated learning, ambient scribe technologies, cultural considerations in care, and how to ensure AI models support rather than replace clinical decision-making. If you're in health system leadership, clinical informatics, operations, or product strategy, this discussion offers frameworks to guide smarter, sustainable AI investments.

AI agents are changing how clinical decisions are made, workflows are optimized, and care is delivered across hospitals, labs, and telehealth systems. Learn how these tools can scale medical expertise, streamline bottlenecks, and improve patient outcomes—without replacing the human element. Hosted by Dr. Sanjay Juneja and featuring expert insights from Dr. Harvey Castro, this interview explains how digital twins, ambient AI, and agentic systems can support clinical judgment, reduce burnout, and personalize care at scale. You’ll also hear practical guidance on whether to build or buy AI tools, how to structure healthcare-specific data, and what integration actually looks like in high-pressure environments. If you’re in healthcare leadership, IT, operations, or product development, this discussion provides frameworks and real-world examples you can act on now.

AI is reshaping rare disease treatments by accelerating drug repurposing, identifying therapeutic opportunities, and unlocking actionable insights hidden in clinical data. Discover how innovative frameworks and technology platforms are helping healthcare leaders, diagnostic companies, and telehealth providers uncover new treatment pathways faster and more efficiently. Dr. Sanjay Juneja (https://sjunejamd.com/) speaks with Dr. David Fajgenbaum (https://www.linkedin.com/in/davidfajgenbaum) about the ethical imperative of using AI-driven drug repurposing to address underserved rare conditions and the growing potential to surface overlooked therapies. Gain practical insights on decision-making, data analysis, and scalable solutions that can impact patient care.

Unlock faster, smarter drug repurposing with open-source data that arms clinicians and researchers with actionable insights. This discussion explores how cutting-edge AI and knowledge graphs are transforming access to potential therapies by ranking 4,000 approved drugs against thousands of diseases - all in record time. Host Dr. Sanjay Juneja speaks with Dr. David Fajgenbaum, Co-founder of Every Cure, to reveal how their platform delivers 75 million computed drug-disease scores directly into the hands of healthcare providers worldwide. Learn how this approach accelerates clinical decision-making, supports evidence-based research, and breaks down barriers to innovative care strategies.

AI prediction is transforming patient care by accelerating how life-saving treatments are identified, repurposed, and delivered to those in need. Discover how cutting-edge data analysis can uncover overlooked therapies and drive faster clinical decisions that impact real-world outcomes. Dr. Sanjay Juneja interviews Dr. David Fajgenbaum, co-founder of Every Cure, to reveal actionable strategies for leveraging artificial intelligence in healthcare systems. Learn how AI-powered frameworks are optimizing treatment selection, guiding clinical workflows, and informing executive decisions across provider networks, telehealth, laboratories, and diagnostics.

The idea that artificial intelligence can uncover life-saving treatments hidden in plain sight is no longer science fiction. In a healthcare system that often favors costly innovation over accessible solutions, using AI to repurpose existing drugs offers a path to faster, affordable breakthroughs. Join Dr. Sanjay Juneja and Dr. David Fajgenbaum, co-founder of Every Cure, as they reveal how AI is accelerating the identification of overlooked therapies for rare and complex diseases. Learn about the critical frameworks behind drug repurposing, how predictive models like Matrix are reshaping disease treatment, and why open-source collaboration could transform healthcare delivery. If you are a physician, healthcare executive, engineer, or healthcare IT leader, this discussion offers essential insights into the future of clinical decision-making.

Explore how data normalization significantly influences AI in healthcare. The conversation dives into the challenges large language models face with medical coding systems like ICD-10. Key insights reveal the essential role of proprietary data and editorial standards in enhancing AI accuracy. Discover how generative AI is transforming data representation through ontologies and knowledge graphs. The synergy of AI with human expertise in managing medical terminology is showcased, promising improvements in the usability of health information.

Data normalization in healthcare isn't just complex – it's mission critical. When a simple lab result like hemoglobin A1C can be recorded under half a dozen different names, clinicians face real obstacles in tracking trends, managing care, and making timely decisions. Mika Newton, CEO of xCures, and Rajiv Haravu, SVP of Product Management at IMO Health, break down why non-standardized data jeopardizes care quality, public health insights, and patient safety. From mismatched lab terms to inconsistent clinical narratives, they explore how definition decay and evolving medical language complicate interoperability and downstream data uses. Learn the frameworks and methodologies IMO Health uses to combat variability – leveraging clinical terminologists, curated content releases, and continuous surveillance of healthcare terminology. Discover how structured and narrative data normalization impacts providers, IT leaders, and healthcare operations.

Rajiv Haravu, SVP of Product Management at IMO Health, dives into the chaotic world of healthcare data. He highlights the challenges of inconsistent documentation and the limitations of AI in addressing these issues alone. The conversation explores the importance of precise tools and editorial standards in data normalization. Rajiv also discusses the evolving definitions in medical terminology and how the integration of AI and traditional methods can improve patient care and research outcomes, ensuring the accuracy of health information.

Emergency rooms are overwhelmed, not just by medical crises, but by the fallout of systemic failures. A growing number of patients are showing up with issues rooted in poverty, housing instability, and food insecurity. AI is helping change that. By connecting underserved patients to billions in unclaimed public benefits, new tools are offering a path to preventative care that begins outside the hospital walls. Dr. Alister Martin explains how AI is being used to bridge the gap between policy and care, reduce avoidable ER visits, and ease pressure on a healthcare system that spends billions treating conditions that could be prevented. When patients get access to the support they already qualify for, outcomes improve - and so does the bottom line.