Digital Pathology Podcast
Aleksandra Zuraw from Digital Pathology Place hosts this podcast that explores digital pathology from foundational concepts to cutting-edge developments, including image analysis and artificial intelligence. The show reviews scientific literature and features discussions with guests about current industry and research trends in digital pathology.
Episodes
250: AI for Scientific Writing: 4 Rules from a Pathologist
Send us Fan MailCan you use AI to write scientific papers without fabricated references, journal trouble or learning to code? I recorded this episode at the airport on my way to ESTP 2026 in Kraków. It's my practice run of the talk I gave there.When deep learning came into pathology, people asked me if I was going to learn to code. I decided no. Large language models kind of proved me right.
249: Cytopathology AI: Crowded-Cell Gaps and LLM Guardrails
Send us Fan MailWhat 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 u
248: Are Foundation Models Really Better for Digital Pathology? Podcast with Panu Kauppila
Send us Fan MailWhat 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 fou
247: Screening Efficiency Over Experience: Rethinking Cytology Expertise
Send us Fan MailDoes 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 yea
246: Computational Pathology Is Changing Companion Diagnostics
Send us Fan MailCan 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 patient
245: Why Going Slow Is Killing Digital Pathology Adoption | Syed T. Hoda, M.D.
Send us Fan MailIs 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 inten
244: Why AI Still Hasn't Revolutionized Drug Discovery (Yet) | Thibault Geoui, PhD
Send us Fan MailIf 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
243: How to Teach AI to Healthcare Professionals | Podcast with Candice Chu
Send us Fan MailWhat 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
242: Foundation Models in Pathology: Strong on Paper, Ready for Labs?
Send us Fan MailAre 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 throu
241: AI-Powered Companion Diagnostics: The Future of Precision Medicine | Podcast with Doug Bowman, VP Precision Medicine at Indica Labs, Inc.
Send us Fan MailHow 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 ex
240: Can AI Copilots Keep Up with Pathologists?
Send us Fan MailCan 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 kin
239: The Four Steps Pathology AI Demos Quietly Skip and Why They Matter
Send us Fan MailWhat 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 th
238: How Do We Know AI Is Ready for Pathology
Send us Fan MailDo 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 th
237: Why Pathology Vendor's Don't Speak the Same Language?
Send us Fan MailWhy 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 actu
236: What Happens When a Patient Sees Their Cancer for the First Time | Podcast with Michele Mitchell
Send us Fan MailWhat 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
235: From Cytology to Omics: Where Pathology AI Gets Harder
Send us Fan MailDigiPath 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 carc
234: Quality, Teaching, and AI: A Practical Shift in Pathology
Send us Fan MailWhere 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 p
233: AI-Driven Breast Cancer Staging in Resource-Constrained Settings
Send us Fan MailPaper 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
232: AI and Digital Pathology in Case-Based Renal Education
Send us Fan MailPaper 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
231: The Future of Bone Marrow Biopsy: Omics and AI Integration
Send us Fan MailPaper 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
230: Artificial Intelligence in Clinical Oncology: Multimodal Integration and Translational Development
Send us Fan MailPaper 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
229: Spatial Omics and AI for Clinically Actionable Cancer Biomarkers
Send us Fan MailPaper Discussed in this Episode:Spatial omics and AI for clinically actionable cancer biomarkers. Reitsam NG. PLoS Med 2026; 23(4): e1005049.Episode Summary: In this deep dive, we explore how artificial intelligence and spatial omics are fundamentally rewriting the rules of cancer diagnostics. We break down a 2026 editorial that challenges a deceptively simple question driving mode
228: GPT-5 and Gemini 2.5 Pro read pathology slides - here is how they did…
Send us Fan MailI 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 a
227: Implementing Generative AI and LLM Assistants in Oncology Practice
Send us Fan MailPaper Discussed in this Episode:How to bring generative AI to oncology practice. D. Truhn & J. N. Kather. ESMO Real World Data and Digital Oncology 2026.Episode Summary:In this journal club deep dive, we step out of the theoretical sci-fi hype of artificial intelligence and look at a practical, real-world roadmap for bringing Generative AI into oncology. We examine a 2026 paper
226: LLM Performance in Cervical Cytology Interpretation: GPT-5 vs. Gemini 2.5
Send us Fan MailPaper Discussed in this Episode: Can large language models like ChatGPT and Gemini interpret cervical cytology accurately? Saroja Devi Geetha. Annals of Diagnostic Pathology 2026; Volume 83, 152641.Episode Summary: In this journal club deep dive, we explore what happens when advanced artificial intelligence is thrown into the visually chaotic realm of human biology. We examine a 20
225: Artificial Intelligence in Oral Oncology: Diagnosis and Therapeutic Integration
Send us Fan MailPaper Discussed in this Episode: Artificial intelligence in oral oncology: Current advances and future potential in diagnosis, prognosis, and therapeutic decision-making. Annamalai A, Dhanes V, Jayalakshmi L, Shanmugam R, Ravi S. Cancer Treatment and Research Communications 47 (2026) 101193.Episode Summary: In this journal club deep dive, we explore how AI is fundamentally reshapin
224: AI and Computational Pathology in Breast Cancer Care
Send us Fan MailPaper Discussed in this Episode: How artificial intelligence applied to digital pathology could guide treatment personalization in breast cancer. T. Ruelle, T. Grinda, L. Del Mastro, M. Lacroix-Triki, B. Pistilli & G. Gessain. ESMO Real World Data and Digital Oncology 2026.Episode Summary: In this journal club episode, we step into the reality of computational pathology and exp
223: You Don’t Need a Scanner to Start Digital Pathology | ACVP Podcast
Send us Fan MailYou 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 remo
222: From Slides to Survival: Can AI Close the Gap?
Send us Fan MailHow 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 squamo
220: UPATHLN: Uncertainty-Aware AI for Pan-Cancer Lymph Node Assessment
Send us Fan MailPaper Discussed in this Episode: High-Sensitivity Pan-Cancer AI Assessment of Lymph Node Metastasis via Uncertainty Quantification. Wang X, Chen Y, Liu X, et al. npj Digit. Med. (2026).Episode Summary: In this episode, we explore a groundbreaking 2026 study that tackles the "black box" problem of medical AI. We dive into UPATHLN, a pan-cancer AI platform for detecting lym
219: POLARIS: Reliable AI Classification and Risk Stratification of Colorectal Polyps
Send us Fan MailPaper Discussed in this Episode:Reliable classification of polyps based on artificial intelligence: a development and validation study. Julbø FMI, Henriksen AL, et al. eClinicalMedicine 2026;93: 103826.Episode Summary:In this journal club deep dive, we explore a groundbreaking 2026 study that tackles the massive bottleneck in gastrointestinal pathology caused by successful colorect
218: AI-Driven Triage for Enhanced Breast Cancer Diagnostic Workflows
Send us Fan MailPaper Discussed in this Episode: A Deep Learning Framework for Automated Triage of Breast Cancer Biopsies in Malaysia: A Simulation Study to Reduce Resource Consumption and Diagnostic Turnaround Time. Yudi Kurniawan Budi Susilo, Dewi Yuliana, Shamima Abdul Rahman, Siew Lian Leong. Clinical Breast Cancer 2026.Episode Summary: In this deep dive, we explore a revolutionary approach to
217: AI vs. Pathologist: Validating Ki-67 Assessment in Pulmonary Neuroendocrine Neoplasms
Send us Fan MailPaper Discussed in this Episode:Ki-67 Proliferation Index in Pulmonary Neuroendocrine Neoplasms: Interobserver Agreement Among Pathologists and Comparison of Two Artificial Intelligence-Based Image Analysis Systems. Teoman G, Turkmen Usta Z, Sagnak Yilmaz Z, Ersoz S. MDPI 2026.Episode Summary:In this journal club deep dive, we step into the lab to examine a direct comparison betwee
216: Multimodal Deep Learning for Predicting Cervical Cancer Survival Outcomes
Send us Fan MailDeep Learning Can Predict the Overall Survival of Cervical Cancer Based on Histopathological Image, Gene Mutation and Clinical Information. Shen J, Miao Z, Wang L, et al. IET Systems Biology 2026.Episode Summary: In this deep dive, we explore a groundbreaking 2026 study that uses multimodal deep learning to act as a "master diagnostician" for cervical cancer. We examine w
215: Pathology-Driven Strategies in Neoadjuvant Immunotherapy for Head and Neck Squamous Cell Carcinoma
Send us Fan MailPaper Discussed in this Episode:Modern Pathology-Driven Strategies in Neoadjuvant Immunotherapy for Head and Neck Squamous Cell Carcinoma: From Residual Tumor Quantification to Spatial and AI-Based Biomarkers. Annabella Di Mauro, Rossella De Cecio, Saverio Simonelli, et al. Cancers (MDPI) 2026.Episode Summary: In this journal club deep dive, we explore a paradigm-shifting 2026 pape
214: AI and Automation in Modern Hematologic Diagnostics
Send us Fan MailPaper Discussed in this Episode: Molecular Pathology, Artificial Intelligence, and New Technologies in Hematologic Diagnostics: Translational Opportunities and Practical Considerations. Alnoor F, Mukherjee S, Menon MP, Ng D, Li P, Ohgami RS. Diagnostics 2026.Episode Summary: In this deep dive, we explore how hematology labs are tackling a massive rise in diagnostic complexity combi
213: Quantitative Regression of qFibrosis with Resmetirom in MAESTRO-NASH Trial
Send us Fan MailPaper Discussed in this Episode:Quantitative regression of qFibrosis with resmetirom: Exploratory histologic endpoints from the MAESTRO-NASH phase III clinical trial. Schattenberg JM, Bedossa P, Guy CD, et al. Journal of Hepatology 2026; https://doi.org/10.1016/j.jhep.2026.03.021.Episode Summary: In this deep dive, we explore how artificial intelligence is revolutionizing the way w
212: Digital Twins in Neuro-Oncology: A Systematic Review
Send us Fan MailPaper Discussed in this Episode: Digital Twins in Neuro-Oncology: A Systematic Review of Current Implementations, Technical Strategies, and Clinical Applications. Annie Singh, Fatima Ahmad Qureshy, Angelica Kurtz, Moinak Bhattacharya, Prateek Prasanna, and Gagandeep Singh. Radiology: Imaging Cancer 2026; 8(2).Episode Summary: In this journal club deep dive, we explore a groundbreak
211: USCAP2026-What Real Life Lab Partnership Looks Like in Digital Pathology with Hamamatsu & Agilent Technologies
Send us Fan MailWhy 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 abou
210: Why Partnerships Matter in Digital Pathology with Hamamatsu
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 shifte
209: USCAP 2026: Digital Pathology 101 With Hamamatsu
Send us Fan MailWhat 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 exhausti
208: A Comprehensive European Colorectal Cancer Cohort Dataset
Send us Fan MailPaper Discussed in this Episode:A comprehensive European Colorectal Cancer Cohort dataset. Holub P, Törnwall O, Garcia Alvarez E, et al. Sci Data (2026). https://doi.org/10.1038/s41597-026-06822-2.Episode Summary: In this journal club edition of the Digital Pathology Podcast, we explore a monumental effort to clear up the diagnostic "muddy waters" of Colorectal Cancer (CR
207: Deep Learning for Histopathological Classification of Salivary Gland Tumors
Send us Fan MailPaper Discussed in this Episode:The Performance of Artificial Intelligence in Classifying Molecular Markers in Adult-Type Gliomas Using Histopathological Images: Systematic Review. Almaabreh O, Al-Dafi R, Tabassum A, Othman A, Abd-alrazaq A. J Med Internet Res 2026; 28: e78377.Episode Summary: In this deep dive of the Digital Pathology Podcast, we explore the intersection of human
206: AI Applications in Oral and Maxillofacial Pathology
Send us Fan MailPaper Discussed in this Episode:Artificial Intelligence and Its Applications in Oral and Maxillofacial Pathology. Veremis B. Dent Clin North Am. 2026 Apr;70(2):403-416.Episode Summary: In this Journal Club edition of the Digital Pathology Podcast, we explore a wild paradox at the bleeding edge of diagnostic medicine. We examine a 2026 paper on artificial intelligence in oral and ma
205: What Makes AI Useful in Pathology Beyond the Demo?
Send us Fan MailWhat 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-w
204: Assessing interstitial fibrosis and tubular atrophy in kidney biopsies artificial intelligence versus humans
Send us Fan MailPaper Discussed in this Episode:Assessing interstitial fibrosis and tubular atrophy in kidney biopsies artificial intelligence versus humans. Farris AB, Zukić D, Solez K. Current Opinion in Nephrology and Hypertension. March 16, 2026.Episode Summary: In this journal club deep dive on the Digital Pathology Podcast, we explore the intense debate over quantifying chronic kidney diseas
203: Clarifying Validation Terminologies in Healthcare
Send us Fan MailPaper Discussed in this Episode:Clarifying validation terminologies in healthcare. Amanda Dy, Sandra M. Buetow, Andrew J. Bredemeyer, et al. npj Digit. Med. (2026). https://doi.org/10.1038/s41746-026-02471-2.Episode Summary:In this deep dive, we unpack the silent chaos surrounding a single, universally used word in healthcare innovation: "validation". Exploring a 2026 pap
202: Deep Learning for Histopathological Classification of Salivary Gland Tumors
Send us Fan MailPaper Discussed in this Episode:Deep learning-based histopathological classification and subclassification of benign and malignant salivary gland tumors. Weber A, Schuster D, Heyer J, Becker C, Burkhardt V, Werner M, Spörlein A, Bronsert P, Schulz T. European Archives of Oto-Rhino-Laryngology 2026.Episode Summary: In this journal club deep dive of the Digital Pathology Podcast, we
201: Confidence-Based AI Pathology for Cholangiocarcinoma Diagnosis
Send us Fan MailPaper Discussed in this Episode:A confidence-based, artificial intelligence pathology model for diagnosis of intrahepatic cholangiocarcinoma. Chang, Jay, Calderaro, et al. Annals of Oncology 2026. DOI: 10.1016/j.annonc.2026.02.018.Episode Summary: In this journal club deep dive, we tackle one of the most frustrating diagnostic puzzles in liver cancer: differentiating primary intrah
200: Artificial Intelligence in Healthcare: From Diagnosis to Rehabilitation
Send us Fan MailArtificial Intelligence in Healthcare: From Diagnosis to Rehabilitation. Witek K, Nowocien M, Gerlach J, et al. Cureus 2026 Jan 25;18(1):e102286.Episode Summary: In this journal club deep dive on the Digital Pathology Podcast, we completely bypass the venture capital hype and science fiction narratives to look strictly at the hard clinical evidence surrounding artificial intelligen
199: Reporting Standards for Medical Foundation and Language Models
Send us Fan MailPaper Discussed in this Episode:Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline. Mese I, Akinci D’Antonoli T, Bluethgen C, et al. Diagn Interv Radiol 2026.Episode Summary: In this special journal club edition of the digital pathology podcast, we tackle a massive structural problem in medical imaging and
198: AI and Multi Omics Upgrade Gastric Biopsies
Send us Fan MailPaper Discussed in this AI Journal Club: "Transforming Gastric Biopsy Diagnostics: Integrating Omics Technologies and Artificial Intelligence" by Nasar Alwahaibi, published in the journal Biomedicines.Episode Summary: In this episode, we explore how traditional gastric biopsies are getting a massive, sci-fi-level upgrade. For over a century, diagnostic practice has relied
197: Optical Biopsies in Gynecologic Oncology surgery
Send us Fan MailPaper Discussed in this AI Journal Club:From Image-Guided Surgery to Computer-Assisted Real-Time Diagnosis with Hyperspectral and Multispectral Imaging: A Systematic Review in Gynecologic Oncology. Innocenzi C, Pavone M, Seeliger B, et al. Diagnostics 2026.Episode Summary:In this journal club deep dive, we explore a groundbreaking 2026 systematic review that challenges the traditio
196: DigiPath Digest #39 - If AI Sees More Than We Do. What Makes It Clinically Trustworthy?
Send us Fan MailIf 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 happen
195: Ultrasound AI Outperforms Surgeons Diagnosing Burns
Send us Fan MailPaper Discussed in this AI Journal Club:Masry ME, Gnyawali S, Jacobson M, Xue Y, Sen C, Wachs J, Gordillo G. AutoMated Burn Diagnostic System for Healthcare (AMBUSH). Plast Reconstr Surg Glob Open. 2023 Oct 18;11(10 Suppl):128-129. doi: 10.1097/01.GOX.0000992564.42240.e3. PMCID: PMC10566867.Episode Summary: In this journal club deep dive, we tackle a clinical problem that has frust
194: Medical Agents Fail Real World Stress Tests
Send us Fan MailPaper Discussed in this AI Journal Club:Benchmarking large language model-based agent systems for clinical decision tasks. Liu, Y., Carrero, Z.I., Jiang, X. et al. npj Digit. Med. 2026.Episode Summary: In this episode, we dive into a comprehensive 2026 benchmarking study that tests whether the highly hyped "Agentic AI" systems are truly ready to revolutionize clinical dec
193: Entropy as a Lie Detector for Radiology
Send us Fan MailPaper Discussed in this AI Journal Club:Wienholt, P., Caselitz, S., Siepmann, R. et al. Hallucination filtering in radiology vision-language models using discrete semantic entropy. Eur Radiol (2026). https://doi.org/10.1007/s00330-026-12384-zEpisode Summary: In this deep dive, we strip away the marketing hype surrounding medical AI and confront the "black box" problem of
221: Deep Learning Triage for Malaysian Breast Cancer Biopsies
Send us Fan MailPaper Discussed in this Episode: A Deep Learning Framework for Automated Triage of Breast Cancer Biopsies in Malaysia: A Simulation Study to Reduce Resource Consumption and Diagnostic Turnaround Time. Susilo YKB, Yuliana D, Rahman SA, Leong SL. Clinical Breast Cancer 2026.Episode Summary: In this journal club deep dive on the Digital Pathology Podcast, we explore a 2026 study tackl
192: AI Detects Hidden Lymph Node Metastases
Send us Fan MailPaper Discussed in this AI Journal Club:Region-Based Segmentation of Lymph Node Metastases in Whole-Slide Images of Colorectal Cancer: A Pilot Clinical Study. Fayzullin A, Savelov N, Balkivskiy A, et al. Cancer Medicine 2026.Episode Summary: In this deep dive, we strip away the marketing gloss of AI as a mere time-saving tool and look at its true value in the lab: saving lives thro
191: Hallucinations, Agents, and AI in Pathology
Send us Fan MailClinical Artificial Intelligence in 2026. Accuracy, Education, and GuardrailsArtificial 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, hallucin
190: Can a Better Stain Improve AI in Pathology?
Send us Fan MailWhat 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 Ingid 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% int
189: Digital Pathology Deployment Decoded the Rigorous 4 Phase Framework
Send us Fan MailSometimes 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
188: AI in Pathology: Biomarkers, Multimodal Data & the Patient
Send us Fan MailIs 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
187: AI vs. Human Pathologists: Who Sees the Biology of Glioblastoma Better?
Send us Fan MailPaper Discussed in this AI Journal Club:Artificial Intelligence-Based Digital Image Analysis for Assessing Ki67, P53, and PHH3 Expression in Glioblastoma Multiforme. Devrim T, Erkilinc G, Tuncer SS. J Coll Physicians Surg Pak 2026; 36(02):153-157Episode Summary: In this journal club deep dive, we step out of the theoretical future of AI and look at a direct, hard-data showdown betw
186: Beyond the Glass Slide – Fusing Pathology and Genomics into 64-Bit Barcodes
Send us Fan MailPaper Discussed in this AI Journal Club: Multimodal learning for scalable representation of high-dimensional medical data. Alsaafin A, Shafique A, Alfasly S, Kalari KR and Tizhoosh HR (2026). Front. Digit. Health 7:1709277. doi: 10.3389/fdgth.2025.1709277Episode Overview In this episode, we tackle the infrastructure challenge in digital diagnostics: how do we efficiently store, sea
185: The Patient's Voice: AI and Digital Pathology in Cancer Care
Send us Fan MailSource Material: This AI journal Club episode is based on the original article, "The patient matters: a roundtable discussion on pathology in the era of digitization and AI," authored by Frederik Deman, Heleen Lauwers, Glenn Broeckx, Roberto Salgado, and Amelie Dendooven (Virchows Archiv, 2026).In this episode, we dive deep into a critical yet often overlooked aspect of m
184: Digital Pathology Guidelines: What Every Lab Must Get Right
Send us Fan MailWhat 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
183: Guidelines for the adoption of digital pathology in clinical pathology units recommended by the polish society of pathologists - AI Publication Review
Send us Fan MailThis AI Journal Club Episode is based on the following paper:Szylberg Ł, Durślewicz J, Chmura Ł, Rezner W, Bartczak A, Marszałek A. Guidelines for the adoption of digital pathology in clinical pathology units recommended by the polish society of pathologists. Diagn Pathol. 2026 Jan 30;21(1):13. doi: 10.1186/s13000-026-01762-2. PMID: 41618426; PMCID: PMC12874716.You can read it here
182: AI, Quality, and Standards: The Next Chapter of Digital Pathology
Send us Fan MailThis 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
181: Can AI Read Clinical Text, Tissue, and Costs Better Than We Can?
Send us Fan MailWhat 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 comput
180: Digital Pathology Recap 2025
Send us Fan MailWhat 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 diagnos
179: How is the BigPicture Project using Foundation Models and AI in Computational Pathology?
Send us Fan MailWhat 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 BigPicture 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
178: Live from London: Essential Digital Pathology & AI Insights 2025
Send us Fan MailWhat 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 highlig
177: From Curiosity to Confidence in Digital Pathology
Send us Fan MailHave 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 person
176: Can AI Protect Patients? Forensics, Pathomics & Breast Cancer Insights
Send us Fan MailWhat 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
175: Deploying Digital Pathology Tools - Challenges and Insights with Dr. Andrew Janowczyk
Send us Fan MailWhy does it take three years to deploy a digital pathology tool that only took three weeks to build? That’s the reality no one talks about—but every lab feels every time they deploy a new tool...In this episode, I sit down with Andrew Janowczyk, Assistant Professor at Emory University and one of the leading voices in computational pathology, to unpack the practical, messy, real-wor
174: How Do We Fix the Bias in Biomedical AI Podcast with Victor CEO and Founder of Omica.Ai
Send us Fan MailWhy are billions of people still invisible in genomic research—and what does that mean for the future of precision medicine?In this episode, I sit down with Victor Angel Mosti, founder and CEO of Omica.Ai, for one of the most insightful conversations I’ve recorded about data equity and building ethical, community-centered AI.Victor shares not only his personal cancer story but also
173: AI and the Human Touch: Patient Safety, Prognosis & Voice Biomarkers
Send us Fan MailHow far can AI go in helping us diagnose disease—without losing the human judgment patients rely on?In this episode, I break down four studies shaping the future of digital pathology, oncology, and neurology. From spatial biology updates at SITC to voice-based Alzheimer’s detection, deep learning for sarcoma prognosis, and new guidelines for safe AI deployment, this week’s digest h
172: Why Structured Reporting Is the Future of Pathology | mTuitive on Workflow, Data & Compliance with Peter O'Toole
Send us Fan MailIf your pathology reports and other data could talk, what would they say about the future of precision medicine? The truth is, most labs already have the data—they’re just not having a conversation with it.In this episode, I talk with Peter O’Toole, President and Chief Software Architect at mTuitive. We recorded live at Pathology Visions and are covering the power of structured dat
171: Real-World Digital Readiness: Turning Stains into Reliable Scans
Send us Fan MailIs your lab truly digitally ready—or just scanning slides?That’s the question I unpack in this live discussion from Day 2 of SITC’s 40th Anniversary Meeting, joined by David Anderson (Biocare Medical) and Don Ariyakumar (Hamamatsu Photonics). Together, we explore what digital readiness really means for multiplex immunofluorescence (mIF) and how to build reliable, reproducible workf
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