Digital Pathology Podcast

Send us a textLeveraging AI for Deep Insights into Tertiary Lymphoid Structures in Colorectal CancerIn this episode of the Digital Pathology Podcast, I introduce 'Aleks + AI,' a new experimental series leveraging Google's Notebook LM to delve deeper into scientific literature. Today's focus is on tertiary lymphoid structures (TLS) and their potential to predict colorectal cancer prognosis. We discuss a study published in the October 2024 issue of Precision Clinical Medicine, exploring different methods of quantifying TLS using digital pathology and AI.  The paper title is: "Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study"The findings highlight TLS density as a reliable predictor of survival and its correlation with immune responses and microsatellite instability. We also touch upon the potential for AI to streamline TLS analysis in clinical settings and the broader implications for personalized medicine. Join us as we dive into the intersection of digital pathology and computer science, featuring insights and commentary from my AI co-hosts, Hema and Toxy.00:00 Welcome and Introduction00:45 Introducing the New AI Tool: Notebook LM by Google01:11 Experimental Series: "Aleks + AI"02:06 Deep Dive into Tertiary Lymphoid Structures (TLS)03:18 Understanding TLS and Their Role in Colorectal Cancer04:20 Quantification Methods and Key Findings05:02 Implications for Personalized Medicine09:02 AI in TLS Analysis and Future Prospects11:00 CMS Classification and TLS Density12:08 Study Limitations and Future Directions15:40 Final Thoughts and Wrap-Up16:28 Feedback and Future PlansTHIS EPISODE'S RESOURCES116: DigiPath Digest #18 | Federated Learning in Pathology. Developing AI Models While Preserving PrivacyPUBLICATION DISCUSSED TODAY📝 Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study🔗https://academic.oup.com/pcm/article/7/4/pbae030/7826772📱 Send us a textSupport the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textIn today's DigiPath Digest, we delve into federated learning, a decentralized approach to AI training that preserves data privacy. I discuss recent papers from PubMed and share my experiences experimenting with AI tools like Perplexity and Gemini for research efficiency. You will also get updates on upcoming plans, including leveraging AI to share more podcasts with you. Did I mention that this is the last livestream of the year as I head to Poland for Christmas? No More DigiPath Digests. We got to number 18 (I overestimated it a bit in the podcast), and you have been instrumental in continuing this series!Big THANK YOU to all the digital Pathology #TRLBLZRS showing up every Friday morning for this!Join me as we tackle the nuances of federated learning and its impact on healthcare and pathology.00:00 Introduction and Greetings00:18 Today's Topic: Federated Learning00:57 AI Tools and Updates04:39 Federated Learning in Detail08:03 Challenges and Benefits of Federated Learning11:21 Exploring More Papers and Future Plans22:53 Wrapping Up and Final ThoughtsLinks and Resources:Subscribe to Digital Pathology Podcast on YouTubeFree E-book "Pathology 101"YouTube (unedited) version of this episodeTry Perplexity with my referral linkMy new page built with PerplexityPublications Discussed Today:📝 Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine🔗https://pubmed.ncbi.nlm.nih.gov/39610333/📝 A review on federated learning in computational pathology🔗https://pubmed.ncbi.nlm.nih.gov/39582895/If you enjoyed this episode, please subscribe and leave a review on your podcast listening App!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textThis episode features a conversation with Dr. Richard Doughty, Senior Medical Advisor at Aiforia Technologies, whose dual training in veterinary and medical pathology offers a unique perspective on the intersections of these fields. Together, we explore the challenges, opportunities, and innovations shaping digital pathology today.What You’ll Learn in This Episode:[00:00:00] Challenges in Pathology TodayDiscussing the pathologist shortage, delayed diagnoses, and how AI can address these issues.[00:03:00] A Pathologist’s Dual PerspectiveDr. Doughty shares his journey of becoming both a veterinary and medical pathologist, and what this means for pathology innovation.[00:08:00] AI’s Role in PathologyInsights into how clinician-centric AI tools like Aiforia are designed to improve diagnostic workflows and outcomes.[00:14:00] Addressing Challenges in AI IntegrationStrategies for overcoming hurdles like algorithm aversion, skill retention, and fostering trust in AI systems.[00:22:00] Preparing Future PathologistsThe importance of incorporating AI training into residency programs and creating a digitally savvy workforce.[00:44:00] How to Implement AI EffectivelyPractical advice on selecting tools, collaborating with providers, and setting realistic goals for AI adoption in practice.Resources and Links Mentioned:Learn More About Aiforia: https://www.aiforia.com/Download Digital Pathology 101Contact Dr. Richard Doughty: [email protected] more videos created together with Aiforia: VIDEO PLAYLISTThis episode is supported by Aiforia Technologies, leaders in AI-powered solutions for digital pathology.Do you know someone who should listen to this episode? Share it with them!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textIn this episode, I sit down with Dr. Nina Kottler, Associate Chief Medical Officer of Clinical AI at Radiology Partners, to dive into the evolving role of AI in radiology and how it can shape the future of digital pathology. Dr. Kottler shares her unique journey, expertise, and practical frameworks for implementing AI that enhance patient care and streamline diagnostic workflows.Episode Highlights and Key Moments:[00:00:45] Introduction to Dr. Nina KottlerDr. Kottler discusses her background in applied mathematics, her journey into medicine, and her work at Radiology Partners, where she combines clinical practice with AI innovation.[00:04:30] Breaking Down Complex Problems in AINina explains her approach to tackling large clinical challenges by breaking them down into manageable parts, a method that’s essential for developing and optimizing AI solutions.[00:08:15] The Role of Data OrchestrationWe dig into “data orchestration” and how ensuring data is aligned with the right AI model is key to producing accurate and reliable clinical outcomes.[00:11:45] Life Cycle of an Exam in RadiologyNina takes us through each step in the radiology workflow—from the initial patient consultation to reporting—and highlights how AI can streamline and enhance each phase.[00:17:00] Evolution of AI Models in HealthcareWe explore how AI has evolved, from early CAD systems to today’s multimodal and transformer models, and the exciting possibilities they bring to both radiology and pathology.[00:23:20] Addressing the Lag in AI Adoption in HealthcareWe discuss the challenge of keeping up with AI advancements while balancing patient safety, regulatory standards, and the need for reliability in clinical settings.[00:27:50] Frameworks for Reducing Variability and Improving AccuracyNina shares actionable frameworks that Radiology Partners uses to reduce variability and improve diagnostic precision—strategies that pathology can learn from.[00:32:40] AI in Workflow Optimization: Where It Has Real ImpactWe discuss specific use cases in clinical workflows that show where AI can bring the greatest value, especially in enhancing patient care through optimized processes.[00:36:50] The Power of Multimodal AI and Vision-Language ModelsCombining large language models with computer vision is moving diagnostics closer to comprehensive, AI-driven care—a promising development we explore in depth.[00:42:15] The Future of Agents in AIWe dive into the concept of “agents” in AI and how these systems may soon coordinate multiple models for more complex and precise clinical analyses.[00:48:10] Where to Learn More about Dr. Nina Kottler’s WorkNina shares where you can catch her upcoming talks and presentations, plus resources for staying updated on the latest in AI for radiology and digital pathology.If you're a pathologist, radiologist, or healthcare professional curious about AI’s impact on diagnostics, this episode is packed with practical guidance on integrating AI into clinical workflows. Join us as we explore how AI is shaping the future of radiology and pathology!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!