Target: Cancer Podcast

Why rely on one method when three are better? Ezra CEO Emi Gal explains how combining imaging, liquid biopsy, and biomarkers creates a superior cancer screening protocol. He also shares how AI enables longitudinal tracking of lesions, reducing false positives and patient anxiety. Learn what makes Ezra's approach uniquely effective in the fight against cancer.

Discover how Ezra uses FDA-cleared AI to transform MRI imaging. CEO Emi Gal explains how Ezra Flash speeds up scan times while improving quality, and how Ezra Assist aids radiologists with accurate annotations. Their AI-powered process makes full-body cancer screening possible in just 22 minutes—for under $500. Learn how this innovation is redefining medical imaging from acquisition to interpretation.

Can patients and clinicians be fairly rewarded for sharing healthcare data? Rajeev Ronanki, CEO of Lyric, discusses a future where AI-enabled tools empower community oncology practices with personalized digital agents. He outlines how reimbursement models can support physicians scaling their care using AI, and why rewarding patient data sharing is both ethical and economically sound.

Ezra CEO Emi Gal breaks down how AI is revolutionizing full-body MRI cancer screening. Learn how FDA-cleared tools accelerate scan time, assist radiologists, and empower patients with easy-to-understand reports—all for just $499. Discover why early detection matters, especially for younger adults, and how Ezra is scaling access to lifesaving diagnostics.

Rajeev Ronanki, CEO of Lyric and former Elevance Health executive, unpacks what the FDA's AI initiative—Elsa—really means for drug innovation and regulation. Rajeev outlines how the agency can use data it already has to drive smarter, faster decisions. He draws powerful parallels to autonomous vehicles and urges the FDA to embrace AI while maintaining scientific rigor.

Trust in AI cannot exist without ethics - and ethics cannot exist without confronting data bias. Discover how artificial intelligence can become a force for safety, fairness, and innovation in healthcare when designed with integrity from the ground up. In this compelling exchange, Dr. Sanjay Juneja (sjunejamd.com) interviews Rajeev Ronanki (LinkedIn), CEO of Lyric, to uncover how AI can be engineered to identify bias, self-evaluate decisions, and evolve into a trusted collaborator in clinical care. They reveal practical strategies for bias detection, the vision of an "AI Hippocratic Oath," and why ethics must precede deployment - especially in medicine. Healthcare leaders, CIOs, CMOs, engineers, and innovators will gain critical insight into governance frameworks that future-proof AI adoption.

Rajeev Ronanki, CEO of Lyric and author of You and AI, joins Dr. Sanjay Juneja to discuss a radical rethinking of payment in healthcare. Instead of upgrading legacy systems, Rajeev proposes bypassing them using trusted AI agents that mediate between EMRs and payers. They explore real-time adjudication, the importance of trust and transparency, and how scalable AI tools can serve even community clinics. Learn how AI is reshaping healthcare finance from the ground up.

AI in healthcare brings breakthroughs - but also new legal and ethical risks. Who's responsible when an AI-assisted diagnosis leads to harm? The licensed physician? The hospital? The tool's developer? As AI becomes embedded in clinical workflows, this question becomes unavoidable. In this conversation, Mika Newton, CEO of xCures (https://www.linkedin.com/in/mikanewton/), interviews Dr. Colleen Lyons, clinical research ethicist (https://aicommons.champlain.edu/people/colleen-p-lyons/), to unpack AI liability in modern healthcare. They explore frameworks for ethical responsibility, institutional risk, informed deployment, and the leadership competencies needed to navigate intelligent failure.

AI is reshaping clinical care, but can we apply trusted bioethical principles to its rapid adoption? This discussion explores how the Belmont Report's three ethical pillars - autonomy, beneficence, and justice - remain essential as AI tools enter diagnosis, decision-making, and patient communication in modern healthcare. Hosted by Mika Newton, CEO of xCures, with expert insights from Dr. Colleen Lyons, a leading clinical research ethicist, the discussion covers informed consent in AI-assisted care, transparency versus explainability, and the ethical implications of asymmetrical power in AI systems. Gain a deeper understanding of how healthcare leaders can navigate AI integration while safeguarding patient rights and institutional trust.

Is AI in healthcare racing toward a crash? Discover what happens when innovation outpaces oversight, and why unchecked growth could lead to another industry meltdown. Mika Newton, CEO of xCures (https://www.linkedin.com/in/mikanewton/), and Dr. Colleen Lyons, clinical research ethicist at Champlain College (https://aicommons.champlain.edu/people/colleen-p-lyons/), unpack the consequences of deregulation and the unintended barriers of over-regulation. They explore the ethics, governance models, and leadership competencies required to navigate the volatile, uncertain, complex, and ambiguous (VUCA) world of AI-driven healthcare. Learn why compliance alone won't future-proof your organization, how to embed ethical frameworks that actually work, and how to recognize when you're stuck in a hype cycle with no real value.

AI transforms how healthcare data is structured, analyzed and applied to clinical decision-making in life sciences. Discover how leading experts harness artificial intelligence to streamline clinical workflows, enhance data quality and accelerate actionable insights for healthcare providers and diagnostic organizations. Mika Newton, CEO of xCures, and Rajiv Haravu, SVP of Product Management at IMO Health, break down practical frameworks for applying AI to complex patient records, from medical coding to interoperability strategies. Understand how AI-driven tools empower healthcare teams to navigate vast medical datasets, improve patient care pathways and support value-based care delivery.

AI is changing healthcare - but are we prepared for the hidden risks? From undermining critical thinking to damaging the human connection between providers and patients, AI's unintended consequences deserve attention. Mika Newton (CEO, xCures) talks with Dr. Spencer Dorn (Vice Chair, UNC Department of Medicine) about the deeper risks AI poses across clinical care, system operations, and provider responsibilities. They explore overlooked dangers: the erosion of professional judgment, reliance on AI-generated summaries, and the threat to personal relationships in medicine. This is essential viewing for leaders navigating AI implementation in health systems.

Dr. Colleen Lyons, a clinical research ethicist with FDA experience, breaks down how ethics must evolve to meet the realities of AI in healthcare. From data bias to transparency, autonomy, and organizational responsibility, she offers an unflinching perspective on where we're falling short - and what must change. Hosted by Mika Newton. Connect with Dr. Lyons: Champlain College Profile. More AI & Healthcare insights: xCures.com

AI is transforming how clinicians handle information, starting with one of the most urgent issues in healthcare: too few providers, too much data, and not enough time. This conversation explores how AI can support physicians by summarizing patient records and medical literature, reducing burnout, and improving clinical decision-making. Hosted by Mika Newton, CEO of xCures (https://www.linkedin.com/in/mikanewton/), the interview features Dr. Spencer Dorn, Vice Chair & Professor of Medicine at the University of North Carolina (https://www.linkedin.com/in/spencerdorn/). He shares powerful insights into AI's current and future role in healthcare delivery—beyond scribing—to information synthesis, predictive analytics, and ultimately better clinical decisions.

AI scribes are transforming how clinical notes are written, relieving physicians from time-consuming documentation and unlocking more patient-focused care. In this video, we explore what AI scribes really do, how they vary in capability, and which features actually move the needle in clinical practice. Hosted by Mika Newton, CEO of xCures (https://www.linkedin.com/in/mikanewton/), and featuring Dr. Spencer Dorn, Vice Chair & Professor of Medicine at the University of North Carolina (https://www.linkedin.com/in/spencerdorn/), the interview outlines how AI scribes differ by integration depth, impact on workflows, and their role in improving documentation accuracy, coding, and even downstream reimbursement.

Precision in surgery doesn't start in the operating room - it starts with the data. Learn how advanced imaging, outcome-linked datasets, and AI-driven insights are reshaping surgical decisions and reducing repeat procedures. Dr. Sanjay Juneja speaks with Adrian Mendes, CEO at Perimeter Medical Imaging AI, to explore the critical relationship between imaging data and post-surgical outcomes in breast cancer care. They break down how image-based machine learning models improve real-time margin assessment, lower costs, and lead to better patient results.

Missed margins and repeat surgeries drive up healthcare costs and stretch critical resources. OCT technology offers a path to smarter imaging and fewer reoperations, cutting costs while improving outcomes. Dr. Sanjay Juneja hosts Adrian Mendes, CEO of Perimeter Medical Imaging AI, to unpack how intraoperative OCT can drastically lower re-excision rates in breast cancer surgery. They explore the ripple effect this has on healthcare economics - from reduced OR time and insurance payouts to stronger patient survival rates. You'll learn how data-backed imaging aligns both clinical and financial priorities.

AI scribes promise relief from clinical documentation fatigue - but what are their limitations, hidden risks, and true return on investment? In a landscape saturated with new scribing technologies, understanding which tools integrate meaningfully with EHR systems and which merely transcribe surface-level dialogue is critical for healthcare leaders. Hosted by Mika Newton, CEO of xCures (https://www.linkedin.com/in/mikanewton/), this discussion features Dr. Spencer Dorn, Vice Chair and Professor of Medicine at UNC (https://www.linkedin.com/in/spencerdorn/), offering clear insights into how AI scribes impact physician workflow, coding accuracy, and care quality. The conversation examines where current tools fall short, highlights the importance of personalization and contextual summarization, and explores how AI may shift the clinician-patient relationship.

Healthcare is shifting fast. If you're not actively learning how to use AI, you're already behind. This discussion reveals how to get the most value out of AI in clinical care, even if you're just starting. Host Dr. Sanjay Juneja (https://sjunejamd.com) sits down with physician-entrepreneur Dr. Harvey Castro (https://www.linkedin.com/in/harveycastromd/) to unpack the critical steps healthcare professionals can take right now to stay relevant and lead with AI. They discuss how to build your AI fluency, what content to follow, how to vet sources, and why a passion for patient care should drive your tech adoption. This is essential viewing for clinical leaders, health IT teams, diagnostics innovators, and telehealth executives ready to make informed decisions in a data-driven world.

AI-assisted imaging is enhancing the precision of breast-conserving surgery by enabling surgeons to reduce re-excisions, preserve healthy tissue, and make more informed intraoperative decisions. Learn how real-time AI models trained on high-resolution optical coherence tomography (OCT) images are transforming how clean margins are assessed during lumpectomies. Adrian Mendes, CEO of Perimeter Medical Imaging, joins Dr. Sanjay Juneja, The OncDoc, to unpack the technological, clinical, and operational implications of using AI to support breast cancer surgery. They cover practical use cases, data strategy, FDA pathways, and cost-savings that matter to hospitals, payers, and diagnostic partners. If you're a provider, technologist, or decision-maker looking to scale smarter surgical care, listen now for valuable insight into what's next in surgical AI.

AI isn't replacing healthcare workers - it's preserving the workforce and extending its reach. From robotic support that reduces physical strain on aging nurses to ambient scribing that eliminates after-hours charting, AI is stepping in where capacity is stretched thin. This conversation explores how AI tools are already shifting care models, enabling clinicians to manage more patients with greater precision and less burnout. Dr. Sanjay Juneja interviews Dr. Harvey Castro, MD, MBA, about practical, near-term applications of AI across clinical environments, including diagnostics, home-based monitoring, and decision support. They discuss real use cases, ethical implications, and a future where physicians spend more time connecting with patients - not keyboards.

Discover how agentic AI is transforming clinical workflows by enabling intelligent digital twins of healthcare professionals that learn, adapt, and act autonomously. This breakthrough supports faster decision-making, reduces bottlenecks, and expands the reach of clinical expertise across provider systems, telehealth, labs, and diagnostic settings. Dr. Sanjay Juneja hosts Dr. Harvey Castro, who explores how agentic systems integrate with wearables, streamline emergency care, and deliver timely medical insights. You'll learn how scalable AI agents enhance operational efficiency and knowledge-sharing without compromising the human touch.

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.

Accurate clinical insights depend on more than just throwing a large language model at a problem. Data normalization and structured medical concepts shape how AI delivers precision in healthcare coding, clinical decision support, and patient care. Mika Newton, CEO of xCures, and Rajiv Haravu unpack how proprietary medical content, editorial policies, and knowledge graphs provide essential context that LLMs alone cannot offer. Learn why healthcare organizations still rely on medical code sets for reimbursement, accurate ICD-10 coding, and decision-making workflows - and how AI-driven agents may soon accelerate ontology creation, dictionary migration, and terminology mapping. Discover actionable frameworks and expert perspectives on leveraging AI in clinical environments to minimize hallucinations, enhance accuracy, and maintain relevance in a rapidly evolving healthcare landscape.

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.

Healthcare data is messy, inconsistent, and buried in narrative. AI sounds like the solution. Until it isn't. In this episode of AI and Healthcare, xCures CEO Mika Newton speaks with Rajiv Haravu, SVP of Product Management at IMO Health, to dissect the real-world challenges of data normalization. From inconsistent documentation of basic lab tests to extracting insights from billions of unstructured notes, Rajiv explains why AI alone falls short - and how precision tools, editorial standards, and clinically-informed design can bridge the gap.

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.

As AI becomes a core part of modern medicine, the way we train future doctors may be due for a serious rethink. Empathy and adaptability, not just chemistry and memorization, could define what makes a good physician in the age of augmented intelligence. With language models becoming standard tools for both patients and providers, skills like prompting, critical thinking, and emotional intelligence may soon matter more than traditional academic benchmarks.

What started with a rabbit heart in a physiology lab led to a career focused on preventing strokes through early detection of atrial fibrillation. A Stanford cardiologist shares how that moment sparked a lifelong interest in cardiac rhythms and how today's wearables can now detect AFib through simple, continuous monitoring, long before symptoms appear. This shift from reactive care to early detection marks a major step forward in heart health, powered by straightforward algorithms and a growing role for AI in predicting cardiovascular risk.

What if your smartwatch could detect a heart condition before you ever felt a symptom? Stanford cardiologist Dr. Euan Ashley reveals how AI and wearables are quietly reshaping the future of healthcare, from spotting silent strokes to redefining what “normal” health looks like. Why do we service our cars and inspect bridges, but wait for our bodies to break down before acting? That question sets the stage for a deep dive into proactive medicine, where tools like the Apple Watch are already catching atrial fibrillation early, and continuous health monitoring could alert us to problems years in advance. Beyond the wrist, AI is transforming everything from clinical documentation to access to specialist care. But big questions remain: Can algorithms be truly equitable? Will personalized prevention ever reach everyone? From ambient AI scribes to the end of “one-size-fits-all” medicine, this is a glimpse into healthcare's next chapter, where your heart might be talking long before you notice.

AI is only as good as the data behind it, and in healthcare, that data is often messy, outdated, and biased. As systems create digital versions of patients, known as twins, the risks increase when data deteriorates or is used without informed consent. Understanding how data breaks down over time, how it's mislabeled or misused, and why clean, well-governed data matters is essential to creating safer, smarter tools that actually work for people, not against them.

Health data is deeply personal, yet it rarely belongs to the individual. Hospitals, labs, tech platforms, and researchers hold the information that defines our health, often without clear consent or transparency. As data grows more valuable, the people it comes from are often excluded from its benefits. Shifting ownership, improving access, and creating real control are essential steps toward giving individuals the power they deserve over their own health information.

AI systems are no longer just tools, they're starting to act on our behalf, powered by our data and often without our awareness. These digital twins, built from lab results, genomes, and behavior patterns, are shaping real decisions in healthcare and beyond. When that data is fragmented, outdated, or biased, the risks multiply. Building systems rooted in truth, transparency, and trust is the only way to ensure these technologies serve us - not replace us.

The future of healthcare data could go in two very different directions. On one side is a system where consent is a checkbox, your data is used without your knowledge, and decisions about care, credit, and access are made by algorithms trained on broken information. On the other is a future where individuals own their data, control how it's used, and benefit from its value. The choice isn't science fiction, it's already being made. Now is the time to decide which future we build.

Emergency rooms are stretched thin, and AI might be the key to making them work better, for patients and clinicians. From ambient AI that cuts down on hours of documentation to large language models that surface critical patient history in seconds, new tools are helping doctors focus on care instead of paperwork. These innovations could ease burnout, reduce delays, and transform how decisions are made in the moments that matter most.

We're entering a future where AI isn't just supporting healthcare - it's shaping decisions, influencing outcomes, and acting on our behalf, often without us even realizing it. These systems are becoming digital twins of real people, powered by everything from lab results to behavior patterns, and the implications are massive. Jason Alan Snyder from Super Truth explains how your health data is being used to build digital versions of you - ones that can make decisions without your knowledge. He breaks down why this matters, how bad data leads to bad outcomes, and what it would look like to actually take control of your data. It's a powerful look at what's really happening behind the scenes in healthcare, and why it affects all of us.

Tackling healthcare costs requires both human connection and smarter use of technology. Dr. Alister Martin emphasizes the importance of trust, the power of patient navigators, and why AI is quickly becoming essential. With a focus on workforce upskilling and sustainable reimbursement models, there's a clear path to reducing ER visits, improving outcomes, and making care more affordable.

AI has the potential to transform healthcare, but adoption remains slow. Outdated IT infrastructure, strict data policies, high implementation costs, and concerns around bias and model performance all stand in the way. Scaling AI in hospitals requires more than just promising tools - it demands infrastructure that supports ongoing governance, transparency, and real-world impact.

Healthcare is drowning in inefficiency - 80% of data is noise, and clinicians waste precious time on tasks that don't improve patient outcomes. But AI is flipping the script. Imagine diagnosing lung cancer in seconds instead of digging through hours of records, or boosting revenue (RVUs) while actually enhancing care quality. Uncover the real barriers to AI adoption and how new platforms are cutting through vendor lock-in to make AI tools accessible in weeks, not months. From radiology to care coordination, AI isn't just the future - it's the lifeline healthcare needs today.

Millions of dollars are being wasted in healthcare every year—not because of a lack of resources, but because people aren't accessing the help that already exists. AI is starting to change that. By streamlining access to underused benefit programs, AI can help patients avoid unnecessary ER visits, reduce hospital strain, and cut costs across the healthcare system. Dr. Alister Martin shares how his work at Link Health is using AI to bridge the gap between patients and public resources, with real-world results backed by recent clinical trials. It's a powerful example of how smart technology can drive both financial and human impact in medicine.

Healthcare costs are rising, but AI could be the key to fixing the system. Beyond improving patient care, AI has the potential to reduce administrative burdens, streamline workflows, and lower overall costs. Dr. Alister Martin has spent years at the intersection of medicine and social change, exploring how technology can make healthcare more efficient and accessible. This conversation looks at how AI-driven solutions can address both the financial and social challenges facing the healthcare industry.

AI adoption in healthcare comes with complexities, from regulatory hurdles to the challenge of building secure, scalable systems that align with hospital needs. Finding the right balance between innovation and data privacy is key to ensuring these technologies can be effectively integrated into medical environments.

AI is transforming healthcare by streamlining medical workflows, enhancing drug development, and driving more efficient, data-driven solutions. Krish Ramadurai shares insights on AI-native health tech, digital pathology, and the challenges of scaling automation in biotech, highlighting the impact of technology on the future of medicine.

Picking the right drugs is a high-stakes game. Get it right more often than the competition, and the rewards are massive. Miss a few, and you're out. So how do top investors and biotech leaders make smart bets? Understanding what pharma actually wants, securing multiple key advocates, and strategically managing risk are all part of the playbook. From clinical-stage assets to investor-backed decision-making, this deep dive unpacks how biotech companies position themselves for success—and what separates the winners from the rest.

AI in healthcare is evolving fast, but how much of it is real progress—and how much is just hype? While AI-driven tools are reshaping clinical workflows and decision-making, many solutions struggle with integration, regulatory hurdles, and real-world adoption. The real winners? Companies that master proprietary data, streamline physician workflows, and build AI solutions that actually work within the constraints of healthcare. From clinical automation to imaging and diagnostics, the impact is undeniable—but replacing doctors? Not happening anytime soon. Where is AI making a real difference, and where is it just noise? Let's break it down.

The future of healthcare is evolving rapidly, and technology is playing a bigger role than ever. Pelu Tran shares insights on how AI, data-driven decision-making, and digital tools are reshaping patient care and the way doctors work. From improving clinical workflows to making healthcare more accessible, these innovations are changing the industry in real time. We also explore the challenges of integrating new technology, the balance between automation and human expertise, and what the next decade of healthcare could look like. How will these advancements impact both patients and medical professionals?