Radiology is experiencing one of the most severe workforce shortages in modern history, and the effects are becoming impossible to ignore.

Dr. Ian Weissman takes us through the full picture: rising imaging demand, younger and sicker patient populations, a decade of increasing CT/MRI utilization, and post‑COVID burnout that accelerated retirements and reduced work hours. He shares how delays in cancer imaging, two-week backlogs, and even temporary outpatient closures are no longer rare, they’re becoming reality.

But the episode is not just diagnostic; it’s prescriptive. Ian emphasizes solutions that can be implemented now: transparent communication with patients, peer learning instead of punitive peer review, servant leadership, and culture-building that encourages respect, safety, and retention.

He also covers long-term strategies such as increasing residency slots, improving visa pathways for international physicians, and the evolving role of interpretive and non‑interpretive AI.

Ian closes on a message of optimism: that with collaboration, leadership, and commitment to patient-centered care, radiology can navigate the crisis and emerge stronger.


What You’ll Learn:

• Why the U.S. is short more than 1,500 radiologists
• How rising imaging volumes and population changes fuel demand
• Why cancer imaging delays are becoming more common
• What moral injury looks like for modern radiologists
• The impact of RVU pressure and nonstop imaging workloads
• How peer learning builds safer, more collaborative teams
• Why AI will support—but not replace—radiologists
• How training pipelines and visa barriers affect the workforce
• What healthcare leaders can do right now to retain clinicians

Chapters:

• [00:00] ICU Backlogs & Outpatient Closures
• [01:38] Introducing Dr. Ian Weissman
• [02:03] The National Radiology Shortage
• [04:54] Cancer Imaging Delays Increasing
• [07:49] How the Crisis Formed: Volumes, Aging, Burnout
• [11:37] Image Overload in the Digital Era
• [13:09] Economic Pressure & Moral Injury
• [15:56] System-Wide Workforce Shortages
• [16:17] Patient Experience: Delays Across Specialties
• [19:37] Global Comparisons: U.S. vs Canada & UK
• [20:20] Solutions: AI, Residencies, Visa Reform
• [26:26] What Strategies Work Today
• [31:09] RETAIN & Leadership Approaches
• [33:00] Peer Learning: Collaboration over Punishment
• [36:43] RSNA’s Workforce & Education Committee (WE)
• [39:23] What Gives Ian Hope
• [42:55] Final Message to Clinicians & Leaders
  
  

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Why are medical physicists, some of the most highly trained problem-solvers in healthcare, drowning in basic, repetitive regulatory work?

In this conversation, Dr. Thomas Griglock breaks down the systemic challenges behind Level 1 task overload, from equipment testing to compliance workflows. He explains how the increasing volume of imaging studies, shrinking workforce pipelines, and continuous new technology adoption have collided to create a time crisis. And in a world where AI is touted as the future of radiology, Tom reveals why most health systems still struggle to implement meaningful automation.

Drawing from his experience in academia, clinical physics, and industry, he shares candid insights on burnout, workforce shortages, and how misaligned decision-making at the leadership level creates costly mistakes. Tom argues that without rethinking time, staffing, and training, AI will continue to fall short, not because the tech isn't ready, but because the people who need to oversee it no longer have the bandwidth.


What You’ll Learn:

• Why Level 1 regulatory tasks dominate physicist workloads
• How stress and burnout come from being pulled away from meaningful, higher-level work
• Why new technology doesn’t automatically save time, and often adds more
• How workforce shortages limit AI adoption and advanced imaging capabilities
• The downstream cost of leadership decisions made without consulting key stakeholders
• Why training and education pipelines will determine the future of imaging innovation
  
  

Chapters:

• [00:00] Introduction — Technology, Stress, and Workflow
• [04:27] The Reality of AI Tools in Clinical Practice
• [08:00] Why New Tech Often Increases Work Instead of Reducing It
• [14:53] Understanding Level 1 Tasks in Medical Physics
• [20:30] Burnout, Bandwidth, and the True Cost of Time
• [26:53] Leaving Academia and the Mid‑Career Reality Check
• [34:19] Workforce Shortages and What’s Actually Possible
• [43:32] Theranostics, Photon‑Counting CT, and Training Needs
• [49:43] Leadership, Vendors, and the Responsibility to Support Change
• [55:29] Closing Thoughts — Why Time Is the Ultimate Limiter
  
  

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The soft skills you bring to imaging are just as critical as your technical expertise.
In this episode of Frame by Frame: Rethink Imaging, host Chris St. John is joined by Dr. Kristin Beinschroth, a radiologic technologist, educator, and researcher, whose recent dissertation explores the connection between moral courage, confidence, and success among radiology students.

Together, they unpack how moral courage predicts stronger academic and clinical outcomes than confidence alone, why students with higher confidence sometimes perform worse, and how educators can teach ethical decision-making through modeling, reflection, and simulation.
Dr. Beinschroth explains how radiology’s unique pressures, from high patient volumes to ethical gray zones, make moral courage essential to professional excellence. She shares how the “See One, Do One, Teach One” framework builds resilience, why nearly 1,800 clinical hours are non-negotiable, and how affective domain teaching can be embedded into an already demanding curriculum.
This conversation challenges traditional views of what defines a “good” technologist, offering a blueprint for cultivating both technical mastery and the moral strength needed to advocate for patients and peers alike.


What You’ll Learn:

• Why moral courage outperforms confidence as a predictor of academic success.
• How to define and recognize moral courage in clinical practice.
• How the “See One, Do One, Teach One” model builds resilience under pressure.
• Why 1,600–1,850 clinical hours are essential to mastering 45 or more clinical competencies.
• Practical ways to teach soft skills and ethics alongside technical rigor.
• Why observation hours and mentorship should complement GPA-based admissions.
• How mentorship, reflection, and vulnerability create future-ready technologists.

Chapters:

[00:00] Intro: Moral Courage in Radiologic Technology[00:02:50] Defining Moral Courage in Clinical Practice[00:04:40] Why Moral Courage Predicts Success Better Than Confidence[00:12:13] Teaching Moral Courage Through Modeling and Simulation[00:17:31] See One, Do One, Teach One: Building Courage Through Fire[00:20:19] Why 1,800+ Clinical Hours Build Resilience, Not Burnout[00:25:48] Weaving Soft Skills Into a Technical Curriculum[00:29:50] Rethinking Admissions: Beyond GPA and Test Scores[00:33:03] The Power of Mentorship in Finding Your Professional Voice[00:36:55] Final Thoughts: Advocating for Better Tech Education
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What does “quality” really mean in healthcare and how do you measure it when every patient’s story is unique?

Dr. Summer Kaplan joins host Chris St. John to unpack the Six Pillars of Healthcare Quality, a framework that continues to guide modern medicine two decades after its creation by the Institute of Medicine.

From her vantage point as a pediatric radiologist, Dr. Kaplan explains how these pillars intersect within medical imaging, revealing how safety, equity, and patient-centeredness are not competing goals but interconnected responsibilities.
She shares personal reflections as both a radiologist and a parent, discusses how over-optimization can erode care, and reminds us that effectiveness in imaging isn’t just about getting the “right diagnosis”—it’s about guiding the next best step for the patient.

Whether you’re a clinician, technologist, or healthcare leader, this episode offers a thoughtful look at what it means to practice imaging that’s safe, equitable, and meaningful for every patient.
What You’ll Learn:

• How the six pillars of healthcare quality, safety, timeliness, efficiency, effectiveness, equity, and patient-centeredness, apply to modern imaging
• Why efficiency has a Goldilocks zone: too little leads to waste, too much leads to burnout and errors
• How patient-centeredness extends beyond the patient to include family-centered care, especially in pediatrics
• What equity in imaging looks like, from resource distribution to race-based utilization differences
• Why effectiveness isn’t always a single diagnosis, it’s directing care down the right pathway
• How clinical guidelines can improve outcomes but are often under-used in practice
• The challenge of measuring quality in systems built for speed rather than reflection
  
  

Chapters:

[00:00] Intro – Defining the Six Pillars of Healthcare Quality[05:23] Safety – Beyond Dose: MRI Safety and Patient Information[13:13] Timeliness – Balancing Wait Times, Workload, and Access[16:45] Patient-Centeredness – Designing Care for Patients and Families[22:34] Equity – Addressing Geographic, Racial, and Socioeconomic Gaps[27:41] Efficiency – The Goldilocks Principle in Radiology[30:28] Effectiveness – When Imaging Guides the Path Forward[35:18] Challenges – Why Measuring Quality Still Isn’t Easy[37:43] Closing – Humanity at the Heart of Imaging

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Spinal CSF leaks are among medicine’s most elusive disorders—often missed, misdiagnosed, or misunderstood. But emerging imaging techniques are changing that narrative.

In this episode of Frame by Frame: Rethink Imaging, host Chris St. John welcomes Dr. Andrew Callen, the pioneering radiologist behind the University of Colorado’s multidisciplinary CSF Leak Program, to discuss how specialized MRI and CT protocols are enabling clinicians to “detect the undetectable.”

Dr. Callen explains how subtle imaging details, like distinguishing fat from fluid through fat-suppressed T2-weighted MRI, can mean the difference between a missed diagnosis and life-changing treatment. He also describes how dynamic CT myelography and innovative patient-positioning techniques are revealing leaks and fistulas invisible to conventional imaging.

Beyond technology, Dr. Callen offers a candid look at the systemic and economic challenges of building a CSF leak program, the importance of multidisciplinary collaboration, and the need to keep an open mind for the patients whose symptoms defy explanation.

Whether you’re a radiologist, neurologist, or healthcare innovator, this episode offers a front-row view into how precision imaging and creative thinking are reshaping our understanding of CSF leaks and patient care.


What You’ll Learn:

• How cerebrospinal fluid (CSF) acts as the brain’s natural cushioning and metabolic system
• Why traditional MRI protocols often miss CSF leaks —and how fat-suppressed T2-weighted imaging improves detection
• How dynamic CT myelography revolutionized leak detection through real-time contrast movement
• The significance of the Myelovator, a patented device that allows controlled patient tilt during CT imaging
• Why CSF–venous fistulas often evade standard imaging and require specialized techniques
• How some CSF leaks can present months or years after a procedure—creating diagnostic complexity
• Why radiologists must balance diagnostic ambition with patient safety and radiation exposure
• The economic and workflow challenges of running a CSF leak program—and how multidisciplinary models help
• Why open-mindedness is critical as medicine continues to uncover new leak types and pathophysiologic mechanisms
  
  
  

Chapters:

[00:00] Intro – Understanding CSF and its role in the brain and spine[04:00] Why CSF leaks are so difficult to detect[07:00] When a “normal” MRI isn’t normal at all[10:15] The MRI Protocol – How fat-suppressed T2 imaging reveals hidden fluid[17:50] Types of CSF leaks and how they can form after procedures[23:40] Dynamic CT Myelography vs Traditional Methods[27:45] Inventing the Myelovator – Innovation born of necessity[31:25] Reshaping workflow and economics for CSF leak programs[36:00] The Future of CSF Leak Research – What we still don’t know[39:00] Closing Thoughts – Hope for patients through imaging innovation
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Innovation in radiology AI isn’t about chasing perfect accuracy, it’s about making AI tools fit seamlessly into clinical workflows to deliver real-world value.

In this episode of Frame by Frame: Rethink Imaging, host Chris St John welcomes Dr. Leonardo Bittencourt, Vice Chair of Innovation at University Hospitals Cleveland and leader of Radically, the radiology AI and diagnostic innovation collaborative. 

With more than 11 years at DASA, Brazil’s largest diagnostic company, and extensive academic expertise, Dr. Bittencourt has built a reputation as a pioneer in validating and implementing AI tools in practice. His work includes global collaborations with startups most notably AZMED, which achieved FDA approval through his structured validation efforts, alongside a strong research background in abdominal radiology and prostate MRI.

The conversation explores why AI solutions that achieve 100% workflow integration at 80% accuracy often outperform tools with higher accuracy but poor usability. Dr. Bittencourt explains how radiology departments can evaluate AI solutions beyond accuracy metrics, focusing instead on patient outcomes, downstream effects, and system-wide impact. 

He also outlines why platform-based AI strategies may be more effective than standalone tools, how structured partnerships create sustainable innovation pipelines, and why hyperacute care settings like stroke and pulmonary embolism are currently the most fertile ground for AI adoption.

Looking forward, Dr. Bittencourt shares how emerging foundation models and large language models are poised to reshape radiology, provided institutions balance technical performance with human factors, cultural readiness, and workflow integration.

For healthcare executives, radiology leaders, and technologists, this episode provides both practical strategies and a long-term vision for bringing AI into practice in ways that improve efficiency, collaboration, and patient care.

What You’ll Learn:

• Why 100% workflow integration with 80% accuracy often outperforms 100% accuracy with poor workflow fit
• How to evaluate AI solutions beyond accuracy metrics by assessing their impact on clinical workflows and patient outcomes
• The strategic advantages of platform solutions vs. standalone AI tools for departments beginning AI adoption
• How to build sustainable academic-industry partnerships through structured validation programs
• Why AI’s greatest impact in radiology is currently felt in hyperacute settings like stroke and pulmonary embolism care
• How emerging foundation models and large language models are poised to transform radiology AI development and deployment
• The importance of measuring AI’s value through system-wide outcomes rather than narrow departmental metrics
• Why successful AI implementation requires understanding downstream effects beyond radiology
  
  

Chapters:

[00:00] Intro: Innovation in Medical Imaging AI with Dr. Leonardo Bittencourt[02:37] From DASA to Academic Medicine: A Journey in Innovation[06:56] The Unique Role of Vice Chair of Innovation[09:21] Building Radically: Creating an AI Innovation Hub[15:39] Why Workflow Integration Trumps Perfect Accuracy in AI[20:16] Evaluating AI Beyond Traditional Metrics[25:15] Platform vs Point Solutions: Strategic Approaches to AI Implementation[31:50] The Future of Foundation Models in Radiology[35:55] Closing Thoughts: The Evolution of AI in Healthcare

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In this episode of Frame by Frame: Rethink Imaging, host Chris St John welcomes Dr. David Larson, Founding Director of the AI Development and Evaluation Lab at Stanford University School of Medicine, to discuss how peer learning is redefining quality assurance in radiology. With over a decade at Stanford and prior leadership roles at Cincinnati Children’s Hospital and Utah Radiology Associates, Dr. Larson has established himself as a pioneer in radiology quality improvement and patient safety. He is best known for developing peer learning as a transformative alternative to traditional peer review, focusing on feedback, learning, and improvement rather than punitive scoring.

The conversation explores why score-based systems often foster adversarial relationships, while peer learning encourages participation, and drives genuine improvement in radiologist performance. Drawing from his extensive experience in dose optimization, technology integration, and medical education, Dr. Larson shares the “three pillars” of effective peer learning and demonstrates how programs can be adapted across different hospital environments—from small rural practices to large academic centers.
They also examine how AI can complement peer learning without undermining the human relationships that drive quality improvement, as well as strategies for building a business case that prioritizes culture and patient safety. With insights spanning program design, interdisciplinary communication, and subspecialty coverage, Dr. Larson makes a compelling case for why local, relationship-based peer learning programs are more effective than national frameworks.

For radiology leaders and practitioners alike, this episode offers both a roadmap and an inspiration for transforming departmental culture through collaborative learning, ensuring that technology and teamwork go hand in hand to improve patient care.
What You'll Learn:

• How to transition from score-based peer review to a collaborative peer learning model
• Why traditional scoring systems create adversarial relationships and hinder genuine improvement
• The three pillars framework for effective peer learning: feedback, learning, and improvement
• How to implement peer learning programs in different hospital settings, from small practices to academic centers
• Why psychological safety and participation metrics matter more than numerical scoring
• How to integrate AI tools with peer learning while maintaining human relationships
• The critical role of interdisciplinary communication in enhancing radiological care quality
• How to build a business case for peer learning that emphasizes cultural improvement and patient safety
• Why local, relationship-based peer learning programs are more effective than national frameworks
• How to adapt peer learning designs for different practice sizes and subspecialty coverage needs
  
  

Chapters:

[00:00] Intro: The Evolution from Peer Review to Peer Learning[02:43] Breaking Free from Score-Based Peer Review Systems[07:50] The Three Pillars: Feedback, Learning & Improvement [13:43] Overcoming Implementation Challenges in Peer Learning[17:40] Adapting Peer Learning for Different Practice Settings[20:15] Structuring Effective Peer Learning Meetings[25:46] Measuring Success Through Cultural Change[29:57] Making the Business Case for Peer Learning[33:02] Building Interdisciplinary Trust Through Shared Learning[35:37] The Future of Peer Learning: AI Integration & Local Focus

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In Part 2 of this two-part series on Frame by Frame: Rethink Imaging, host Chris St John welcomes back medical physicist Brad Lofton, CEO of Colorado Associates in Medical Physics and a recognized thought leader in imaging physics. 

Lofton brings extensive experience from both academic centers and community hospitals, where he has advanced Medical Physics 3.0 initiatives and championed quality management programs that reshape how physics supports patient care.

Building on Part 1’s diagnosis of the challenges facing the profession, Lofton dives into actionable strategies for repositioning medical physicists as collaborative problem-solvers rather than compliance checkers. He underscores the importance of emotional intelligence (EQ) alongside technical expertise (IQ), highlighting how relationship-building with radiologists and administrators is critical to embedding physicists into clinical operations.

The discussion explores how continuous quality monitoring and real-time assurance technologies can replace outdated pass/fail testing, allowing physicists to identify and prevent issues before they impact patients. Lofton also addresses the operational and financial literacy needed for physicists to demonstrate value to healthcare leaders, ensuring they are seen as contributors to both quality and efficiency.

A strong advocate for healthcare equity, Lofton emphasizes that rural and community hospitals deserve the same caliber of physics support as major academic institutions. He shares innovative models for delivering high-quality physics services in resource-constrained environments, helping bridge gaps in access.

For executives and imaging professionals, this conversation offers a roadmap for transforming medical physics into a problem-solving specialty that elevates patient care, strengthens departmental performance, and secures the future of the profession.

What You’ll Learn:

• Why medical physics must evolve beyond annual compliance checks to continuous quality improvement
• How to apply Medical Physics 3.0 principles for patient-centered imaging care
• The importance of building collaborative relationships with radiologists and administrators
• Why emotional intelligence (EQ) is just as crucial as technical expertise (IQ) for physicists
• How to leverage new tools for real-time quality monitoring in radiology
• Pathways to repositioning physics as a problem-solving specialty, not just a compliance function
• Why understanding operations and finances increases physicists’ impact and credibility
• Strategies for expanding high-quality physics support to rural and community hospitals
  
  

Chapters:

[00:00] Intro and Welcome to Frame by Frame[00:49] Evolving Role of Medical Physicists in Healthcare[03:39] Understanding Physics 3.0 and Patient-Centered Care[06:35] Real-Time Quality Monitoring and CMS Requirements[09:49] Breaking Away from Traditional Approaches[15:36] Shifting from Compliance to Value Creation[18:34] Building Better Relationships Between Physicists and Clinical Staff[22:33] Rethinking Dose Optimization and Clinical Protocols[24:59] Vision for the Future of Medical Physics[28:31] Closing Thoughts and Rural Healthcare Challenges

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In Part 1 of this thought-provoking two-part episode of Frame by Frame: Rethink Imaging, host Chris St John welcomes Brad Lofton, CEO of Colorado Associates in Medical Physics (CAMP), for a candid conversation about the crossroads facing medical physics today.

Lofton, a seasoned leader in diagnostic and nuclear medical physics, argues that the profession has been held back by a narrow focus on regulatory compliance, often reduced to annual inspections and machine testing, rather than fully embracing its potential as a driver of quality in patient care.

Together, they explore how historical inertia and over-standardization have commodified physics services, eroding the profession’s perceived value. Lofton explains why the future of the field depends on moving from Level 1 work, basic compliance, to Level 2 and Level 3 physics that deliver measurable improvements in outcomes, efficiency, and safety. 

The discussion highlights the need for continuous monitoring, trending analysis, and closer collaboration with radiologists, rather than relying solely on pass/fail threshold testing.

The conversation also touches on emerging opportunities for medical physicists to integrate into AI-driven imaging, image-guided surgery, and other advanced technologies, areas where their expertise can directly impact patient outcomes. Lofton emphasizes that rural and community hospitals deserve the same caliber of physics support as academic medical centers, and he shares strategies for bridging that gap.
For professionals committed to elevating the role of physics in healthcare, Part 1 offers both a diagnosis of the current challenges and the foundation for a roadmap that will be expanded in Part 2, where they’ll dive deeper into actionable solutions for transforming the field.

What You'll Learn:

• Why medical physics must transition from machine-focused compliance to patient-centered quality management
• How historical inertia and commodification have limited the profession’s perceived value
• The distinctions between Level 1 (compliance) and higher-level physics work that drives real improvement
• Why annual testing alone is insufficient for modern imaging quality assurance
• How medical physicists can serve as quality managers rather than just inspectors
• The role of trending analysis and real-time monitoring in preventing issues before they affect patients
• How to integrate physics expertise into emerging technologies like AI and image-guided surgery
• Ways to improve risk communication with patients, providers, and radiologists
• Why equal access to high-quality physics support is essential for rural and community hospitals
• Strategies for building stronger, more collaborative partnerships between physicists and radiologists
  
  

Chapters:

[00:00] Intro: The Crisis in Medical Physics[02:35] From Med School Dreams to Medical Physics[06:19] Evolution of Imaging Physics: A Decade of Change[11:29] The Personal Crisis: Machine Focus vs Patient Care[17:52] Market Forces vs Clinical Innovation in Medical Imaging[24:00] Understanding Level 1, 2 and 3 Physics Work[31:00] Redefining Value: From Compliance to Quality Management[37:15] Communication and Risk: Building Better Clinical Partnerships[41:05] Closing Thoughts & Preview of Part 2
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In this episode of Frame by Frame: Rethink Imaging, host Chris St John welcomes Dr. Woojin Kim, an expert at the intersection of radiology and AI innovation, to discuss the future of generative AI in medical imaging. As Chief Strategy Officer at HOPPR and Chief Medical Officer at the ACR Data Science Institute, Dr. Kim draws from deep experience in both clinical practice and healthcare entrepreneurship.
Together, they explore the growing capabilities of AI in radiology, from automated draft reporting for chest X-rays and CT scans to the emerging potential of Agentic AI as a true assistant within clinical workflows. Dr. Kim emphasizes that while AI holds the promise of boosting efficiency, with some studies reporting 15.5% gains, it must be grounded in personalization and supported by human oversight to avoid risks like hallucinated results.

The conversation dives into practical mechanisms for safe integration, including Model Context Protocols (MCPs) that embed clinical nuance into AI outputs, and the need for hands-on experience over purely theoretical exposure. Dr. Kim also addresses the regulatory and liability gaps that could hinder responsible adoption, advocating for frameworks that can keep pace with innovation.
For professionals navigating the AI landscape in healthcare, this discussion offers a forward-looking yet grounded perspective on building meaningful human-AI partnerships, where technology enhances rather than replaces clinical judgment.
If you enjoyed this episode, don’t forget to subscribe and leave a review. It helps us reach more imaging professionals and healthcare leaders around the world.

What You'll Learn:

• How automated draft reporting for chest X-rays and CT scans is becoming a reality, with early studies showing 15.5% efficiency gains
• Why personalization in AI-generated radiology reports is crucial for widespread adoption and clinical effectiveness
• The critical importance of preventing AI hallucinations in medical reporting through human-in-the-loop workflows
• How Model Context Protocols (MCPs) are enabling more sophisticated AI integration in radiology workflows
• Why Agentic AI could transform radiology by functioning as an intelligent assistant rather than a replacement
• How to balance AI implementation with clinical expertise while maintaining focus on patient care and safety
• The importance of hands-on experience with AI tools rather than just theoretical knowledge
• Why regulatory and liability frameworks need to catch up with AI advancement in medical imaging

Chapters:

00:00 Intro: Meet Dr. Woojin Kim, Pioneer in Medical AI00:07:25 The Reality of AI-Generated Radiology Reports00:14:27 Why Personalization Matters in AI Reports00:21:12 Managing AI Hallucination Risks in Medical Imaging00:27:47 Current Barriers to GenAI Implementation00:30:31 Understanding Agentic AI in Radiology00:36:27 Model Context Protocols: The Future of Integration00:43:48 Key Takeaways: Learning to Work With AI in Healthcare

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