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Welcome back to the DigiPath Digest, fresh from PathVision! In this episode we will dive into the latest updates from the PathVision conference, covering trends in AI-driven diagnostics, the expansion of digital pathology into primary care, and the exciting new frontier of glassless pathology.
Join me as I recap the highlights of PathVision and the latest updates from the digital pathology literature, including discussions on:
AI Integration in Pathology: Learn how AI is advancing breast cancer diagnostics with tools like Ki-67 scoring models and multi-label AI for mammography, aimed at reducing unnecessary biopsies.
Global Health & Digital Microscopy: Hear about innovative projects from Sweden and Finland focused on AI-supported digital microscopy in primary healthcare labs, bringing accessible diagnostics to underserved areas.
Glassless Pathology with MUSE: Discover how glassless pathology is changing tissue imaging with MUSE (Microscopy with UV Surface Excitation), enabling diagnostics without the need for traditional glass slides. Dr. Zuraw breaks down what this means for future pathology workflows.
Plus, a shout-out to the vendors and partners making these advancements possible, and insights from Dr. Zuraw’s conversations with digital pathology trailblazers from around the globe, including new developments from Asia in digital pathology education and technology.
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**Publications Discussed Today:📝 AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Protocol for a Scoping Review🔗https://pubmed.ncbi.nlm.nih.gov/39486020/📝 Ki-67 evaluation using deep-learning model-assisted digital image analysis in breast cancer🔗https://pubmed.ncbi.nlm.nih.gov/39478421/📝A Multi-label Artificial Intelligence Approach for Improving Breast Cancer Detection With Mammographic Image Analysis🔗https://pubmed.ncbi.nlm.nih.gov/39477432/📝 A comprehensive evaluation of an artificial intelligence based digital pathology to monitor large-scale deworming programs against soil-transmitted helminths: A study protocol🔗 **https://pubmed.ncbi.nlm.nih.gov/39466830/If you enjoyed this episode, please subscribe and leave a review to
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