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Digital Pathology PodcastAuthor: 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. Language: en-us Genres: Health & Fitness, Medicine, Natural Sciences, Science Contact email: Get it Feed URL: Get it iTunes ID: Get it Trailer: |
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182: AI, Quality, and Standards: The Next Chapter of Digital Pathology
Episode 182
Sunday, 8 February, 2026
Send us a textThis 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 about hype. It’s about standards, validation, data integrity, and clinical translation—the factors that decide whether AI tools stay in research or reach patient care.Episode Highlights01:21 – Practical digital pathology adoption guidelines (Polish Society of Pathologists)08:05 – AI in liver cancer imaging & pathology, and why framework alignment matters18:10 – AI-generated tissue maps as metadata for WSI archives23:01 – PathQC: predicting RNA integrity and autolysis from H&E slides32:14 – ML-assisted IHC scoring in genitourinary cancers29:42 – Digital Pathology 101 book + community updatesKey TakeawaysDigital pathology adoption still requires clear standards and validation workflowsAI performs best when aligned with existing diagnostic frameworks (e.g., LI-RADS)Metadata extraction is a low-effort, high-impact AI use caseSlide-based quality control can support biobanking and biomarker researchAutomated IHC scoring improves consistency—but adoption remains uneven globallyResources Mentioned Digital Pathology 101 (free PDF & audiobook)Publication Links: a. https://pubmed.ncbi.nlm.nih.gov/41618426/ b. https://pubmed.ncbi.nlm.nih.gov/41616271/ c. https://pubmed.ncbi.nlm.nih.gov/41610818/ d. https://pubmed.ncbi.nlm.nih.gov/41595938/ e. https://pubmed.ncbi.nlm.nih.gov/41590351/ Support the showGet the "Digital Pathology 101" FREE E-book and join us!
