Podcast
AI and Healthcare
Hosted by Tensor Black · EN
AI and Healthcare—with Mika Newton and Dr. Sanjay Juneja is an engaging interview series featuring world-renowned leaders shaping the intersection of artificial intelligence and medicine. Discover how AI is transforming healthcare today, addressing real-world challenges and improving patient outcomes.
This series caters to anyone’s listening style with bite-sized, commute-friendly insights and full-length interviews. Join co-hosts Mika Newton, CEO of xCures, and Dr. Sanjay Juneja, a globally recognized oncologist and VP of Clinical AI at Tempus AI, as they explore cutting-edge innovations with industry pioneers.
Originally launched as the TARGET: Cancer Podcast in 2021, the series evolved after 75 episodes into a comprehensive platform for AI and healthcare conversations.
This series caters to anyone’s listening style with bite-sized, commute-friendly insights and full-length interviews. Join co-hosts Mika Newton, CEO of xCures, and Dr. Sanjay Juneja, a globally recognized oncologist and VP of Clinical AI at Tempus AI, as they explore cutting-edge innovations with industry pioneers.
Originally launched as the TARGET: Cancer Podcast in 2021, the series evolved after 75 episodes into a comprehensive platform for AI and healthcare conversations.
14episodes
Episodes
Newest firstAll episodes
What If Every Patient Had a Digital Twin? Part 2
1w ago00:31:29Tap to summarizeWhat 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.
Transcribe →Can We Detect Cancer Before Symptoms Appear? Part 1
3w ago00:42:53Tap to summarizeCancer 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.
Transcribe →Could Sleep Affect Cancer Survival?
May 1900:51:27Tap to summarizeCancer 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.
Transcribe →AI Is Changing Healthcare — But At What Cost?
Apr 2900:44:29Tap to summarizeAI 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?
Transcribe →What Clinical AI Is Doing Well... and Where It Still Needs Work
Apr 1700:59:51Tap to summarizeAI 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.
Transcribe →Why Most AI Startups Fail in Healthcare
Apr 1400:41:30Tap to summarizeAI is exploding in healthcare — but most startups still fail. In this episode of the AI & Healthcare Podcast, Dr. Sanjay Juneja speaks with innovation leaders Dr. Bernardo Perez-Villa and Dr. Peter Alperin about the reality of building successful medical technology in 2026. Hundreds of AI tools have FDA clearance, billions have been invested in digital health, and yet hospitals still struggle to adopt new technology. Why?
Transcribe →The Payment Crisis Behind Healthcare
Apr 1000:51:03Tap to summarizeCare is delivered every day in American hospitals, but getting paid for that care has become a battle. Denials, prior authorization, billing complexity, and rising costs have created a financial crisis behind the scenes of modern medicine. Insurance companies use automation to control payments, while hospitals struggle to keep up. Now AI is entering the fight. Dr. Sanjay Juneja and Dr. Douglas Flora speak with Monique Lappas, Founder and CEO of Qualify Health, about the growing war over who pays for care and how intelligent automation is helping providers recover lost revenue, reduce patient debt, and keep hospitals from closing.
Transcribe →How AI Creates Precision in Mental Health Care
Feb 1300:53:09Tap to summarizeMental health is now central to high-quality cancer care, yet access, diagnostic precision, and scalability remain major gaps. In this in-depth discussion, clinical and innovation leaders explore how artificial intelligence can shift mental health care from reactive support to precision-driven, proactive intervention. The conversation examines AI as a clinical signal amplifier that enhances human judgment without replacing it. Topics include objective diagnostics, functional brain mapping, digital phenotyping, therapeutic bots, longitudinal monitoring, and how AI can better match patients to the right level of care at the right time. The discussion also addresses real-world implementation challenges in oncology and health systems, including workforce shortages, equity, and clinical oversight.
Transcribe →Clinical AI Governance: What Clinicians Must Know in 2026
Jan 1500:53:18Tap to summarizeAI in healthcare is accelerating fast—but adoption without governance is risk. In this conversation, oncology and health policy leaders break down how clinicians and health systems should evaluate emerging AI tools: what FDA clearance vs approval really means, why “not FDA-approved” doesn’t automatically mean unsafe, and how laboratory-developed tests (LDTs) are already embedded in everyday care. We also explore real-world evidence, model drift, and why implementation—not innovation—is the true bottleneck for safe scale. If you’re assessing AI in imaging, diagnostics, clinical decision support, or workflow automation, this is your framework for asking smarter questions and protecting patients.
Transcribe →How Digital Twins Could End Medical Guesswork
Dec 1800:52:48Tap to summarizeDigital twins are moving from engineering into healthcare and the implications are profound. From oncology decision-making to clinical trials and personalized medicine, virtual human twins could reshape how clinicians predict outcomes, reduce toxicity, and tailor treatment. Dr. Sanjay Juneja and Dr. Doug Flora are joined by digital twin leaders Jim St. Clair and Professor James Fargason to explore how real-time data, AI, and system-level modeling can move medicine beyond population averages toward individualized care. This conversation unpacks what a true digital twin requires, why data quality and interoperability matter, and how digital twins may accelerate drug development, improve trial design, and reduce moral injury for clinicians.
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