Send us Fan Mail Paper 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 heavily on visual pattern recognition via histomorphology—essentially looking at stained tissue under a br...
Mar 11, 2026•13 min•Ep. 198
Send us Fan Mail Paper 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 traditional intraoperative frozen section. We examine how hyperspectral and multispectral imaging are fu...
Mar 10, 2026•23 min•Ep. 197
Send us Fan Mail 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...
Mar 09, 2026•27 min•Ep. 196
Send us Fan Mail Paper 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 frustrated surgeons for decades: accurately diagnosing burn depth. We examine a groundbreaking study i...
Mar 06, 2026•26 min•Ep. 195
Send us Fan Mail Paper 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 decision-making. We pit baseline large language models (LLMs) against complex, multi-agent systems in a series...
Mar 06, 2026•20 min•Ep. 194
Send us Fan Mail Paper 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-z Episode Summary: In this deep dive, we strip away the marketing hype surrounding medical AI and confront the "black box" problem of Vision Language Models (VLMs) like GPT-4o. We examine a groundbreaking 2026 study published in European Rad...
Mar 04, 2026•23 min•Ep. 193
Send us Fan Mail Paper 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 through relentless vigilance. We examine a 2026 study on colorectal cancer that deploys a two-stage A...
Mar 02, 2026•22 min•Ep. 192
Send us Fan Mail 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 deploymen...
Mar 02, 2026•30 min•Ep. 191
Send us Fan Mail 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 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% interobserver variability persists in Gleason grading and how optimized stains combined with explain...
Feb 24, 2026•56 min•Ep. 190
Send us Fan Mail 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?” , ...
Feb 24, 2026•23 min•Ep. 189
Send us Fan Mail 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] Commun...
Feb 21, 2026•21 min•Ep. 188
Send us Fan Mail Paper 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):153-157 Episode Summary: In this journal club deep dive, we step out of the theoretical future of AI and look at a direct, hard-data showdown between artificial intelligence and the human eye. We examine a groundbreaking 2026 study on Glioblas...
Feb 20, 2026•20 min•Ep. 187
Send us Fan Mail Paper 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.2025.1709277 Episode Overview In this episode, we tackle the infrastructure challenge in digital diagnostics: how do we efficiently store, search, and integrate the overwhelming amount of multimodal data generated by modern medicine? We ta...
Feb 20, 2026•20 min•Ep. 186
Send us Fan Mail Source 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 medical technology: the patient's perspective on the rapid integration of Digital Pathology (DP) and Artifici...
Feb 20, 2026•22 min•Ep. 185
Send us Fan Mail 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 m...
Feb 20, 2026•34 min•Ep. 184
Send us Fan Mail This 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: https://pubmed.ncbi.nlm.nih.gov/41618426/ You can view the YouTube version with captions here: ...
Feb 09, 2026•15 min•Ep. 183
Send us Fan Mail 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 not...
Feb 08, 2026•26 min•Ep. 182
Send us Fan Mail 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 cost...
Jan 24, 2026•35 min•Ep. 181
Send us Fan Mail 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 hype and ...
Dec 31, 2025•23 min•Ep. 180
Send us Fan Mail 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 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 enable thousands by making high-quality, legally compliant data accessible at scale. We unpack wha...
Dec 17, 2025•1 hr 6 min•Ep. 179
Send us Fan Mail 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...
Dec 11, 2025•40 min•Ep. 178
Send us Fan Mail 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 show w...
Dec 10, 2025•20 min•Ep. 177
Send us Fan Mail 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 referen...
Dec 05, 2025•29 min
Send us Fan Mail Why 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-world truth behind deploying, validating, and accrediting digital pathology tools in the clinic. We w...
Dec 02, 2025•1 hr 13 min•Ep. 175
Send us Fan Mail Why 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 the staggering truth: Hispanic and Latino populations make up less than 1% of genomic datasets. ...
Nov 18, 2025•55 min•Ep. 174
Send us Fan Mail How 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 highlights where AI is making a real impact—and where caution still matters. Episode Highlights 1️⃣...
Nov 18, 2025•30 min•Ep. 173
Send us Fan Mail If 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 data and how it’s redefining the future of pathology reporting, AI, and clinical decision support. W...
Nov 11, 2025•38 min•Ep. 172
Send us Fan Mail Is 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 workflows that scale from research to clinical settings. What We Discuss The Discovery Funnel I open ...
Nov 08, 2025•23 min•Ep. 171
Send us Fan Mail Can spatial biology and multiplex immunofluorescence truly transform how we understand cancer? I went live from the Society for Immunotherapy of Cancer (SITC) 2025 — the 40th Anniversary Meeting to explore how spatial biology, multiplex IF, and digital pathology are coming together to redefine cancer diagnostics, research, and precision medicine. This session kicked off a weekend of cutting-edge discussions with leaders from Hamamatsu (Booth 415) and Biocare Medical (Booth 717) ...
Nov 07, 2025•23 min•Ep. 170
Send us Fan Mail Can one AI system learn from every organ — and teach us something new about all of them? In this edition of DigiPath Digest #31 , I explore how artificial intelligence is transforming pathology across multiple organ systems , revealing connections that help us diagnose faster, more consistently, and more accurately than ever before. From glomerulonephritis to hepatocellular carcinoma , AI is no longer confined to a single specialty — it’s becoming the connective tissue between t...
Nov 03, 2025•38 min•Ep. 169
