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© 2025 Digital Pathology Podcast
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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.
160 Episodes
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Send us a text What if the way we quantify pathology is more guesswork than science? In this episode of DigiPath Digest, I take you through the latest research where AI is not just supporting but challenging traditional methods of image analysis in neuropathology, nephrology, hematology, and cytology. From Boston brain banks to Mayo Clinic kidney models, we look at how advanced AI compares to human vision—and where it already outperforms us. Episode Highlights: [00:02:49] Neuropathology image...
Send us a text What if the AI tools we trust for cancer diagnosis are not always correct? This episode of DigiPath Digest takes on the uncomfortable but critical question: can AI “lie” to us—and how do we verify its performance before adopting it in clinical practice? Highlights: [00:02:00] Foundation models in action: Deployment of a fine-tuned pathology foundation model for EGFR biomarker detection in lung cancer—reducing the need for rapid molecular tests by 43%.[00:08:41] Bone marrow AI m...
Send us a text What if AI could predict cancer outcomes better than traditional methods—and at a fraction of the cost? In this episode, I explore how multimodal AI is reshaping lung and prostate cancer predictions and why integration challenges still stand in the way. Episode Highlights with Timestamps: [00:02:57] Agentic AI in toxicologic pathology – what it is and how it could orchestrate workflows.[00:05:40] Grandium desktop scanners – making histology studies more accessible and efficient...
Send us a text “AI in Pathology Isn’t Coming — It’s Already Here. Are You Ready?” From confusion to clarity — that’s what this episode is all about. I sat down with Drs. Liron Pantanowitz, Hooman Rashidi, and Matthew Hanna to dissect one of the most important and comprehensive AI-in-pathology resources ever created: the 7-part Modern Pathology series from UPMC’s Computational Pathology & AI Center of Excellence (CPAiCE). This isn’t just another opinion piece — it's your complete guide to ...
Send us a text Can AI Grade Cancer Better Than Us? The Truth About T-Cell Imaging, Biomarkers & Digital Pathology Disruption You think Saturday mornings are for coffee? Try diving into bone marrow morphology, organ donor kidney biopsies, and AI-driven metastasis detection at sunrise. That’s how I do it—and you’re invited to join. Welcome to another data-packed episode of DigiPath Digest, where we explore the latest frontier in digital pathology and AI. This time, I reviewed some of the m...
Send us a text AI Pathology & Genomics: A New Benchmark for Predicting Gene Mutations If you still think visual quantification is “good enough” in pathology, think again. In this 27th episode of DigiPath Digest, I break down four transformative abstracts that show how AI is shifting our diagnostic landscape—from breast cancer segmentation to fibrosis assessment, and all the way to spatial immunology and the evolving immunoscore. If you’re still relying on manual scoring, static staging s...
Send us a text If our visual scoring is still based on gut feeling, how do we scale precision? In this week’s DigiPath Digest, I explored four new AI-focused papers that could reshape how we diagnose prostate, bladder, gastroesophageal, and endocrine cancers. From automated IHC scoring to predicting urethral recurrence post-cystectomy, these studies highlight the growing value—and responsibility—of integrating AI into our pathology workflows. And yes, I also reveal where to get my histology-...
Send us a text If we don’t learn to work with LLMs now, we might end up competing with them. 🧠 In this week’s DigiPath Digest, I return to our Journal Club to unpack the latest research on AI in tumor classification, focusing on GPT-4o, LLaMA, and other LLMs. Can these models really outperform traditional tools when analyzing pathology reports? Surprisingly—yes. But don’t panic. This episode is about understanding what LLMs actually bring to the table, how they’re being evaluated, and what w...
Send us a text AI in Pathology: ML-Ops and the Future of Diagnostics What if the most advanced AI models we’re building today are doomed to die in the machine learning graveyard? 🤯 That’s the haunting question I tackled in the final episode of our 7-part series exploring the Modern Pathology AI publications. In this session, I explored machine learning operations (ML-Ops)—what they mean for digital pathology —and why even the most brilliant algorithm can fail without proper deployment strateg...
Send us a text Can We Ever Eliminate Bias in AI for Pathology? Every time we think we’ve trained a “neutral” algorithm, we discover our own fingerprints all over it. Our biases. Unconscious. Systemic. Data-driven. And if we ignore them, AI won’t just fail—it will fail patients. Welcome back, my digital pathology trailblazers! In this sixth episode of our 7-part AI in Pathology series, we tackle one of the most uncomfortable yet necessary conversations: Ethics and Bias in AI and Machine Learni...
Send us a text The Most Overlooked Risk in AI for Pathology? It’s Not What You Think… Welcome, my trailblazing digital pathologists! In this episode, I dive headfirst into the regulatory maze of Artificial Intelligence (AI) in pathology, covering global frameworks, safety risks, ethics, and the future of software as a medical device. While regulation might not be the flashiest part of AI, ignoring it could cost us innovation—or worse, patient safety. We’re on Part 5 of our 7-part AI in Pathol...
Send us a text In this episode sponsored by Epredia, Dr. Anil Parwani explores the transformative journey of digital pathology from basic slide scanning to AI-driven diagnostics. He shares real-world implementation experiences and demonstrates how these technologies are addressing critical challenges in pathology practice. Pathology faces increasing demands amid workforce shortages and knowledge explosionDigital pathology provides standardization, objectivity, and automation beyond glass sl...
Send us a text You might be using AI models in pathology without even knowing if they’re giving you reliable results. Let that sink in for a second—because today, we’re fixing that. In this episode, I walk you through the real statistics that power—and sometimes fail—AI in digital pathology. It's episode 4 of our AI series, and we’re demystifying the metrics behind both generative and non-generative AI. Why does this matter? Because accuracy isn't enough. And not every model metric tel...
Send us a text What if I told you the biggest AI breakthroughs in pathology aren’t coming from ChatGPT or generative tools—but from the quiet power of predictive analytics and machine learning? In this episode, I explore the non-generative side of artificial intelligence in pathology. These are the tools that detect tumors, segment tissue, classify images, and make predictions—without generating a single word. It’s the third chapter in our guided AI series, and this time we focus on the model...
Send us a text ❗️Is synthetic data trustworthy enough to train AI for patient care? It just might be—and that's what both excites and terrifies me. ❗️ Hey trailblazers! In this episode of the Digital Pathology Podcast, I take you through the second part of our AI in Pathology series—this time, we’re focusing on generative AI and how it’s revolutionizing diagnostics, education, and workflow in our field. From synthetic H&E slides that could pass for real to multimodal agents that can read ...
Send us a text Generative vs. Non-Generative AI in Pathology: Why the Difference Matters If we don’t start defining what kind of AI we’re talking about, we risk letting buzzwords replace real science. 🧠 This is where we begin—at the foundation. Welcome to the first episode of our 7-part Guided Journey through AI in Pathology, inspired by two must-read articles from Modern Pathology that you’ll want bookmarked forever (links below 👇). In this episode, I clarify one of the most misunderstood d...
Send us a text Will FDA rules disrupt the way we diagnose diseases? In this episode, I break down a seismic shift in lab medicine: a federal court has vacated the FDA’s controversial rule classifying lab-developed tests (LDTs) as medical devices. This change carries serious implications for innovation, digital pathology, AI-based diagnostics, and small labs across the U.S. 🎧 What You’ll Hear: What LDTs are and why they matter for rare diseases and personalized medicine Why the FDA rul...
Send us a text You think going digital in pathology just means buying a scanner? Think again. In this episode sponsored by Epredia, I sat down with Ryan Davis, Director of Global Business Strategy at Epredia, to talk about what it really takes to implement digital pathology—and why modularity, cytology support, and AI integration are changing the game. Whether you’re starting your digital journey or scaling up with advanced tech, there’s something in this conversation for yo...
Send us a text In this episode, I talk with Tiffany Chen, MD, and Ben Cahoon from Techcyte about Fusion, their new digital pathology platform. Fusion integrates clinical and anatomic pathology workflows, AI algorithms, and electronic health records—all into one streamlined experience. We explore how Fusion simplifies case management, improves diagnostic accuracy, and brings AI-powered pathology into routine practice. Plus, we discuss the importance of open standards, partnerships with Mayo C...
Send us a text Why do so many digital pathology tools stall before they ever reach patients? In this USCAP 2025 special sponsored by Muse Microscopy, I talk with Esther Abels, founder of SolarisRTC, regulatory strategist, and the force behind the first FDA-cleared whole slide imaging system. We break down what startups and established companies must do from day one to succeedbin getting their devices through the FDA. Hint: regulatory strategy isn’t a final step—it’s your starting l...
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