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PODCAST

Digital Pathology Podcast

Aleksandra Zuraw, DVM, PhD

Aleksandra Zuraw from Digital Pathology Place discusses digital pathology from the basic concepts to the newest developments, including image analysis and artificial intelligence. She reviews scientific literature and together with her guests discusses the current industry and research digital pathology trends.

science natural sciences

All Episodes

24:15

228: GPT-5 and Gemini 2.5 Pro read pathology slides...

Digital Pathology Podcast ·

2026/04/11

Send us Fan Mail I did something I've never done before for this episode — I went live from the middle of a national park. This is DigiPath Digest #42, broadcasting from the Great Sand Dunes National Park in Colorado via Starlink from my family road trip. Yes, it actually worked. And so did the papers. This episode covers four papers that all ask the same uncomfortable question from different angles: how close is AI to being genuinely useful in real pathology practice — and what's still stand...

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15:55

223: You Don’t Need a Scanner to Start Digital...

Digital Pathology Podcast ·

2026/04/08

Send us Fan Mail You don't need a fancy scanner, a huge budget, or a computational background to get started in digital pathology. That's what I told the ACVP podcast — and I meant it. In this episode, I share my full digital pathology journey: from being completely intimidated by scanners during residency, to building a career that combines toxicologic pathology, image analysis, and remote work at a global CRO. If you're a resident, a trainee, or even a seasoned pathologist who hasn't fully ...

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40:36

222: From Slides to Survival: Can AI Close the Gap?

Digital Pathology Podcast ·

2026/04/06

Send us Fan Mail How close is pathology AI to making decisions that matter in real workflows, real trials, and real patient care? In this episode of DigiPath Digest, I review five recent papers that approach that question from very different angles. We look at multimodal survival prediction in cervical cancer, pathology-driven response assessment in neoadjuvant immunotherapy for head and neck squamous cell carcinoma, AI-assisted Ki-67 scoring in pulmonary neuroendocrine neoplasms, automation ...

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16:31

211: USCAP2026-What Real Life Lab Partnership Looks...

Digital Pathology Podcast ·

2026/03/30

Send us Fan Mail Why do digital pathology projects get harder once the real workflow starts? In this USCAP 2026 conversation, I talk with Robert Moody from Hamamatsu and Jake Eden from Agilent about what the conference theme, MAKING CONNECTIONS, looks like in actual digital pathology implementation. This was not just a conversation about products. It was a conversation about workflow. We talked about why consistent staining matters before scanning, why strong partnerships need a shared vision...

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15:31

210: Why Partnerships Matter in Digital Pathology...

Digital Pathology Podcast ·

2026/03/27

Send us Fan Mail Why does digital pathology adoption move faster in some places than others? In this USCAP 2026 conversation, I sat down with Robert Moody and Fumiya Fuji from Hamamatsu to talk about what the conference theme, MAKING CONNECTIONS, really looks like in practice. This was not just a scanner conversation. It was a workflow conversation. We talked about why digital pathology has shifted from a scanner-first mindset to a solution-first one, and why that matters fo...

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14:01

209: USCAP 2026: Digital Pathology 101 With Hamamatsu

Digital Pathology Podcast ·

2026/03/23

Send us Fan Mail What makes digital pathology feel so hard to enter, even for smart people already working around it? In this special USCAP conversation, Stephanie Fullerton from Hamamatsu turns the tables and interviews me about Digital Pathology 101 — the book I wrote for people who are starting or continuing their digital pathology journey. We talk about why the book is not meant to be an exhaustive manual, but a practical framework. A way to help people see the full picture, ask better qu...

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33:23

205: What Makes AI Useful in Pathology Beyond the Demo?

Digital Pathology Podcast ·

2026/03/21

Send us Fan Mail What happens when AI looks strong in a paper, but the workflow still isn’t ready? In DigiPath Digest #40, I reviewed five recent papers across kidney pathology, oral and maxillofacial pathology, glioma biomarker prediction, digital twins in neuro-oncology, and a major European colorectal cancer cohort. A common theme kept coming back: good performance is not the same thing as real-world readiness. We started with kidney biopsies and the challenge of assessing interstitial fib...

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26:40

196: DigiPath Digest #39 - If AI Sees More Than We...

Digital Pathology Podcast ·

2026/03/09

Send a text If AI can detect patterns we cannot see, how do we know when its answers are clinically trustworthy? In this episode of DigiPath Digest #39, I explore a big-picture question in digital pathology and medical AI. Many models now match or even exceed human performance in specific diagnostic tasks. But most of that evidence comes from controlled or retrospective datasets. So what happens when we try to bring these tools into real clinical workflows? I review four recent papers that he...

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30:19

191: Hallucinations, Agents, and AI in Pathology

Digital Pathology Podcast ·

2026/03/02

Send a text Clinical Artificial Intelligence in 2026. Accuracy, Education, and Guardrails Artificial intelligence is evolving fast in medicine. But how accurate is it. And are we building it safely? In this episode of DigiPath Digest, I review five new studies shaping digital pathology, radiology, burn diagnostics, and agent-based large language model systems. We discuss accuracy gains, hallucination filtering, education challenges, and why safeguards are essential before clinical deployment....

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55:50

190: Can a Better Stain Improve AI in Pathology?

Digital Pathology Podcast ·

2026/02/24

Send a text What if one of the biggest sources of diagnostic variability in prostate cancer isn’t the pathologist—but the stain we’ve trusted for decades? In this episode, I speak with Professor Ingied Carlbom, founder of CADESS.AI, about a different way to approach prostate cancer grading—by rethinking staining, segmentation, and AI decision support from the ground up. We explore why 30–40% interobserver variability persists in Gleason grading and how optimized stains combined with explainab...

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22:38

189: Digital Pathology Deployment Decoded the...

Digital Pathology Podcast ·

2026/02/24

Send a text Sometimes a paper comes out that’s so practical and relevant to what we do in digital pathology that I know we have to talk about it. In this episode, I dive into “A Guide for the Deployment, Validation and Accreditation of Clinical Digital Pathology Tools” from Geneva University Hospital (HUG) — one of the most useful, real-world frameworks I’ve seen for bringing digital pathology tools safely into clinical practice. If you’ve ever built an AI model and wondered, “Now what?”, thi...

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21:14

188: AI in Pathology: Biomarkers, Multimodal Data &...

Digital Pathology Podcast ·

2026/02/21

Send a text Is AI in pathology actually improving diagnosis — or just adding complexity? In DigiPath Digest #37, we reviewed four recent publications covering AI-based biomarker quantification in glioblastoma, real-world digital workflow integration in prostate cancer, multimodal AI combining histopathology and genomics, and patient perspectives on AI in cancer diagnostics. This episode connects technical performance with something equally important: trust. Episode Highlights [00:02] Communit...

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34:27

184: Digital Pathology Guidelines: What Every Lab...

Digital Pathology Podcast ·

2026/02/20

Send a text What actually needs to be in place before digital pathology can replace the microscope? In this episode of DigiPath Digest, I walk through the 2026 Polish Society of Pathologists guidelines and translate them into practical steps for real pathology labs. This isn’t theory. It’s about hardware fidelity, data integrity, validation, and AI integration — and what each of these actually requires in daily workflow. We talk about scanner resolution standards (≤0.26 μm per pixel), 4K moni...

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25:57

182: AI, Quality, and Standards: The Next Chapter of...

Digital Pathology Podcast ·

2026/02/08

Send us a text This session is a practical walkthrough of where digital pathology and AI truly stand in early 2026—based on five recent PubMed papers and real-world implementation experience. In this episode, I review new clinical adoption guidelines, AI applications in liver cancer imaging and pathology, AI-ready metadata for whole slide images, non-destructive tissue quality control from H&E slides, and machine learning–assisted IHC scoring in precision oncology. This conversation is no...

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34:59

181:Can AI Read Clinical Text, Tissue, and Costs...

Digital Pathology Podcast ·

2026/01/24

Send us a text What happens when artificial intelligence moves beyond images and begins interpreting clinical notes, kidney biopsies, multimodal cancer data, and even healthcare costs? In this episode, I open the year by exploring four recent studies that show how AI is expanding across the full spectrum of medical data. From Large Language Models (LLM) reading unstructured clinical text to computational pathology supporting rare kidney disease diagnosis, multimodal cancer prediction, and cos...

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23:15

180: Digital Pathology Recap 2025

Digital Pathology Podcast ·

2025/12/31

Send us a text What really changed in digital pathology this year—and what still needs work? As we close out 2025 and step into 2026, I wanted to pause, reflect, and share what I’ve seen shift from theory to real-world practice across labs, conferences, and clinical workflows. I look back at the most meaningful developments in digital pathology and AI in 2025—from wider adoption of primary diagnosis on digital slides to more grounded, evidence-driven use of AI tools. We’ve moved past ...

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66:23

179: How is the Big Picture Project using Foundation...

Digital Pathology Podcast ·

2025/12/17

Send us a text What if the biggest breakthrough in pathology AI isn’t a new algorithm—but finally sharing the data we already have? In this episode, I’m joined by Jeroen van der Laak and Julie Boisclair from the IMI Big Picture consortium, a European public-private initiative building one of the world’s largest digital pathology image repositories. The goal isn’t to create a single AI model—but to enable thousands by making high-quality, legally compliant data accessible at scale. We unpack w...

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40:17

178: Live from London: Essential Digital Pathology &...

Digital Pathology Podcast ·

2025/12/11

Send us a text What if the biggest transformation in digital pathology this year had nothing to do with new hardware—and everything to do with how we think about value, workflow, and readiness? In this year-end recap livestream from the 11th Digital Pathology & AI Congress in London, I break down what truly mattered in 2025. Instead of focusing on buzzwords or hype cycles, this episode highlights the practical advances shaping diagnostics, patient care, and drug development—and the mindse...

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19:41

178: From Curiosity to Confidence in Digital Pathology

Digital Pathology Podcast ·

2025/12/10

Send us a text Have you ever thought, “Digital pathology sounds amazing, but without a scanner, what’s the point of learning it now?” If so, this episode will change how you see your role in the future of pathology. In this talk, I challenge one of the most persistent myths in our field: the belief that you need expensive hardware before you can begin your digital pathology journey. Through personal experience and the remarkable story of another pathologist who started with even less, I...

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28:44

176: Can AI Protect Patients? Forensics, Pathomics &...

Digital Pathology Podcast ·

2025/12/05

Send us a text What happens when AI becomes powerful enough to diagnose—not just one disease, but entire fields of medicine at once? In this episode of DigiPath Digest #33, I break down four new PubMed abstracts shaping the future of digital pathology, clinical AI integration, federated learning, and multidisciplinary cancer care. Across every study, one message is clear: AI is accelerating, but human oversight defines its safe adoption. Below are the full timestamps, key insights, and refer...

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196 results

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