Digital Pathology Podcast

Jaksot

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  249: Cytopathology AI: Crowded-Cell Gaps and LLM Guardrails 31.08.2026 30min

  Send us Fan Mail What happens when AI models that perform almost perfectly on scattered cervical cells become less reliable than a coin flip on crowded cell groups? In DigiPath Digest #51, I examine what this performance gap tells us about artificial intelligence in cytopathology. The first paper evaluated six convolutional neural network models trained to distinguish benign from high-grade lesions using scattered cervical cytology cells. The models achieved AUCs ranging from 0.950 to 0.996 o...
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  248: Are Foundation Models Really Better for Digital Pathology? Podcast with Panu Kauppila 20.08.2026 52min

  Send us Fan Mail What good is a powerful foundation model if it slows the pathologist down, can’t explain its result, or doesn’t fit the clinical workflow? Foundation models are gaining attention across digital pathology. But they’re not finished clinical tools by themselves. In this episode of the Digital Pathology Podcast, I speak with Panu Kauppila, Chief Product Officer at Aiforia, about what foundation models are, how they differ from traditional convolutional neural networks, and what i...
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  247: Screening Efficiency Over Experience: Rethinking Cytology Expertise 17.08.2026 28min

  Send us Fan Mail Does more experience automatically make a cytotechnologist more accurate—or does where they look first matter more? In DigiPath Digest #50, I review a digital cytology eye-tracking study that challenges the assumption that diagnostic accuracy improves steadily with years of practice. The researchers tracked the visual behavior of 100 board-certified cytotechnologists with 1 to 40 years of experience. They found no statistically significant linear relationship between years of...
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  246: Computational Pathology Is Changing Companion Diagnostics 13.08.2026 1t 6min

  Send us Fan Mail Can a treatment decision depend on whether one pathologist sees 45% biomarker positivity and another sees 55%? Visual immunohistochemistry scoring helped establish precision oncology. But as targeted therapies become more sensitive to subtle biological differences, categorical scores such as 0, 1+, 2+, and 3+ may no longer capture the information needed to identify the right patients. In this episode, I speak with three Roche experts: Gordana Juric-Sekhar, MD, anatomic pathol...
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  245: Why Going Slow Is Killing Digital Pathology Adoption | Syed T. Hoda, M.D. 29.07.2026 44min

  Send us Fan Mail Is your digital pathology rollout moving so slowly that it’s creating a fragmented workflow instead of transforming the department? In this episode of the Digital Pathology Podcast, I speak with Dr. Syed Hoda, Director of Digital Pathology at NYU, about why gradual implementation may no longer be the best approach to digital pathology adoption. Dr. Hoda explains how NYU used an intensive nine-month planning period to prepare for a department-wide transition. The process invol...
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  244: Why AI Still Hasn't Revolutionized Drug Discovery (Yet) | Thibault Geoui, PhD 22.07.2026 1t 36min

  Send us Fan Mail If AI is already being used across the drug development pipeline, why hasn’t its impact matched the investment? AI can help researchers review scientific literature, predict protein structures, prioritize molecules, assess toxicity, support clinical trials, and monitor adverse events. But access to better tools doesn’t automatically create better drugs. In this episode, I speak with Thibault Geoui, Science CDO and host of the Tech & Drugs Podcast, about where AI is making...
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  243: How to Teach AI to Healthcare Professionals | Podcast with Candice Chu 02.07.2026 44min

  Send us Fan Mail What does AI literacy actually look like for pathologists, researchers, and future clinicians? And how do you teach it in a way that is practical, not abstract? In this episode, I talk with Candice Chu, DVM, PhD about something I think a lot of people in digital pathology and computational pathology are feeling right now: AI is moving fast, but education is still catching up. Candice is a clinical pathologist, veterinarian, and educator building AI-focused teaching and r...
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  242: Foundation Models in Pathology: Strong on Paper, Ready for Labs? 24.06.2026 44min

  Send us Fan Mail Are pathology foundation models actually ready for labs, or are they still stronger on paper than in practice? In this episode of DigiPath Digest #49, I unpack a timely review on pathology foundation models and ask the question that matters most to me: not just what these models can do, but what has to be true before they are genuinely useful in real pathology workflows. I walk through how pathology AI moved from narrow, task-specific models into the era of transformer-based ...
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  241: AI-Powered Companion Diagnostics: The Future of Precision Medicine | Podcast with Doug Bowman, VP Precision Medicine at Indica Labs, Inc. 16.06.2026 42min

  Send us Fan Mail How far can pathologists take visual biomarker scoring before human vision becomes the bottleneck? In this episode, I talk with Doug Bowman. PhD, VP Precision Medicine at Indica Labs, about what happens when companion diagnostics move from traditional visual scoring into the era of AI-powered image analysis. Doug comes from a biomedical and electrical engineering background, with experience in microscopy, digital image analysis, pharma workflows, and now precision medicine at...
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  240: Can AI Copilots Keep Up with Pathologists? 03.06.2026 35min

  Send us Fan Mail Can AI copilots really keep up with pathologists when the cases are new, the workflow is messy, and the benchmark is actually protected from leakage? In this episode of DigiPath Digest #48, I focus on one paper: DALPHIN: Benchmarking Digital Pathology AI Copilots Against Pathologists on an Open Multicentric Dataset. I chose this paper because I think the field needs more of this kind of work. Less hype. More evaluation. Less “look what AI can do.” More “how do we test it in a...
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  239: The Four Steps Pathology AI Demos Quietly Skip and Why They Matter 28.05.2026 48min

  Send us Fan Mail What happens when a pathology AI model misses the tissue before it even begins—and can better segmentation, education, and virtual staining close the gaps? In DigiPath Digest #47, I review four recent studies that expose both the promise and the weak points of AI-assisted digital pathology. We start with a step that sounds simple: detecting tissue on a whole slide image. Yet when that first step fails, the downstream algorithm may miss cancer entirely. From there, I look at a...
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  238: How Do We Know AI Is Ready for Pathology 19.05.2026 20min

  Send us Fan Mail Do you really need a scanner, whole slide images, and AI infrastructure before you can start in digital pathology? In this episode, I argue that you do not. I’m Dr. Aleksandra Zuraw, veterinary pathologist and digital pathology educator, and this talk is about a belief I hear all the time: I don’t have the tools yet, so there is no point learning digital pathology. I used to think that too. When I was training in Berlin, there was one Leica 6-slide scanner, and it felt like d...
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  237: Why Pathology Vendor's Don't Speak the Same Language? 18.05.2026 35min

  Send us Fan Mail Why are pathology vendors still speaking different image languages when radiology solved that problem decades ago? In this episode of DigiPath Digest #46, I talk through four papers that all point to a bigger issue in digital pathology: we are not only dealing with better algorithms. We are dealing with interoperability, workflow design, explainability, and whether the field is actually ready to use these tools well. I start with DICOM in digital pathology, because I think th...
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  236: What Happens When a Patient Sees Their Cancer for the First Time | Podcast with Michele Mitchell 15.05.2026 1t 14min

  Send us Fan Mail What if the most frightening part of a pathology report is not the word cancer, but the silence that follows? In this episode of the Digital Pathology Podcast, Dr. Aleksandra Zuraw talks with Michele Mitchell—breast cancer survivor, caregiver, national patient advocate, and longtime volunteer across Michigan Medicine, ASCP, the Digital Pathology Association, and MyPathologyReport.ca—about what happened when she saw her own cancer slide years after treatment. That moment chang...
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  235: From Cytology to Omics: Where Pathology AI Gets Harder 12.05.2026 34min

  Send us Fan Mail DigiPath Digest #45 asks a practical question: can AI in pathology move from correlation to real clinical use? In this episode, I review four papers that push on that question from different angles: computational pathology moving toward morphology-driven molecular inference, the current state of digital cytopathology and AI, multi-omics and precision oncology in hepatocellular carcinoma, and AI literacy in veterinary education. What ties them together is not model performance...
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  234: Quality, Teaching, and AI: A Practical Shift in Pathology 25.04.2026 37min

  Send us Fan Mail Where is AI in pathology actually becoming useful right now? In this episode of DigiPath Digest, I review 4 new PubMed papers across digital pathology, whole slide imaging (WSI), computational pathology, medical education, forensic pathology, and breast cancer AI. We look at a deep learning tool for coronary artery stenosis measurement in forensic autopsies, an AI-powered digital pathology model for renal pathology education, an open-source quality control tool for prostate b...
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  233: AI-Driven Breast Cancer Staging in Resource-Constrained Settings 24.04.2026 22min

  Send us Fan Mail Paper Discussed in this Episode: Deep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings. Bedőházi Z, Biricz A, Kilim O, et al. Journal of Pathology Informatics 21 (2026) 100644. Episode Summary: Welcome back, Trailblazers! In this Journal Club deep dive of the Digital Pathology Podcast, we flip the core assumption of microscopic precision on its head. Can an AI accurately predict pathological breast cancer s...
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  232: AI and Digital Pathology in Case-Based Renal Education 22.04.2026 18min

  Send us Fan Mail Paper Discussed in this Episode: Integrating AI-Powered Digital Pathology With Case-Based Teaching: A Novel Paradigm for Renal Education in Medical School. Zhou H, Cui L. Clin Teach 2026; 23(3):e70421. doi: 10.1111/tct.70421. Episode Summary: In this journal club episode tailored for healthcare trailblazers, we explore a massive paradigm shift in medical education. We examine a 2026 perspective article that uses the notoriously complex field of renal pathology as a stress tes...
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  231: The Future of Bone Marrow Biopsy: Omics and AI Integration 19.04.2026 21min

  Send us Fan Mail Paper Discussed in this Episode: Advancements in bone marrow biopsy: the role of omics and artificial intelligence in hematologic diagnostics. Maryam Alwahaibi and Nasar Alwahaibi. Front. Med. 2026; 13:1772478. Episode Summary: In this journal club deep dive, we explore a paradigm shift in hematopathology, moving from 19th-century visual assessments to the cutting edge of precision medicine. We examine a 2026 review that unpacks how combining artificial intelligence with mult...
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  230: Artificial Intelligence in Clinical Oncology: Multimodal Integration and Translational Development 19.04.2026 21min

  Send us Fan Mail Paper Discussed in this Episode: Artificial intelligence in clinical oncology: Multimodal integration and translational development. Ruichong Lin, Zhenhui Zhao, Zhonghai Liu, Jin Kang, Kang Zhang, Xiaoying Huang, Yunfang Yu. Cancer Letters 2026; Volume 649, 218493. Episode Summary: In this journal club deep dive, we explore how cutting-edge AI is fundamentally rewriting the rules of cancer diagnostics. We examine a comprehensive 2026 review on clinical oncology that highlight...