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In this episode of the Digital Pathology Podcast, I sit down with Dr. Lija Joseph, a pathologist who is redefining patient care by making pathology more accessible and understandable. Traditionally, pathology has been a “behind-the-scenes” specialty, but Dr. Joseph is changing that by directly engaging with patients, showing them their pathology slides, and empowering them with knowledge about their diagnoses.
🔬 Key Topics Covered:
[00:00:00] Introduction to Patient-Centric Pathology[00:01:00] Meet Dr. Lija Joseph: Her Background and Journey[00:05:00] The Patient Who Inspired a New Approach[00:10:00] Why Patients Need to See Their Pathology Images[00:15:00] The Power of Knowledge: How Patient Awareness Improves Care[00:20:00] Overcoming Barriers to Patient-Pathologist Communication[00:25:00] How Digital Pathology Can Make This Scalable[00:30:00] The Role of Technology in Breaking Down Access Barriers[00:35:00] Convincing Healthcare Leadership to Support This Initiative[00:40:00] How Digital Pathology Can Transform Patient Outcomes🩺 Why This Matters:
Most patients never meet their pathologists—but should they? Dr. Joseph believes so. She shares powerful stories of how patients who see their own slides gain a deeper understanding of their disease, make better treatment decisions, and experience greater peace of mind.🚀 How Digital Pathology Can Change the Future:
Dr. Joseph’s approach is innovative, but digital pathology can take it even further. Imagine a world where patients don’t have to visit a hospital to see their biopsy results but can access them remotely through secure digital platforms. This technology has the potential to bridge the gap between patients and their pathologists, improving care and trust.🎧 Tune in now to learn how pathology can become more patient-focused!
#DigitalPathology #PatientCenteredCare #PathologyInnovation #AIinHealthcare
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Transforming Pathology: A Deep Dive into the Muse System
This episode is sponsored by Muse Microscopy.
In this episode, we explore the primary challenge of implementing digital pathology globally—digitizing the analog.A potential solution is direct-to-digital pathology, exemplified by the MUSE system by Muse Microscopy. This technology eliminates the need for glass slides and manual staining, offering rapid, non-destructive imaging of intact tissue samples.
You will learn about the advantages of Muse, including faster diagnostics, improved data fidelity, and broader accessibility, particularly in remote areas.
Detailed insights into the Muse workflow, imaging techniques, and potential applications in human and veterinary medicine are provided.
Challenges like adoption barriers and regulatory hurdles are also addressed. Join us as we explore how the Muse system is redefining diagnostic workflows and enhancing patient outcomes.
00:00 Introduction to Digital Pathology
00:18 The Hurdle of Digitizing Analog Pathology
00:26 Direct to Digital Pathology: A Game Changer
01:46 Introduction to Muse Microscopy
02:32 How Direct to Digital Pathology Works
03:10 Advantages of Direct to Digital Pathology
04:13 Understanding Muse Technology
05:26 The Digital Pathology Workflow with Muse
14:15 Challenges and Misconceptions
15:38 The Future of Pathology
16:31 Frequently Asked Questions
18:07 Conclusion and Additional Resources
18:54 Behind the Scenes and Final ThoughtsLinks and Resources:
Original blog post on Digital Pathology Place Website and LinkedInYouTube playlist with more information about MUSESmartPath Product presentation from CAP 2024Video showing the SmartPath device at the conference boothUSCAP in Boston - Muse Microscopy booth #528Support the show
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In this episode of the Digital Pathology Podcast, I take a deeper dive into Generative AI in Pathology, following the AI in Pathology series published by USCAP. AI has already begun transforming medical diagnostics, but what does Generative AI mean for digital pathology? From synthetic data generation to multimodal AI models, this episode explores the cutting edge of AI’s role in pathology and how it’s evolving to enhance efficiency, accuracy, and patient care.
🔬 Key Topics Covered:
[00:00:00] Introduction – The Evolution of AI in Pathology[00:02:00] Acknowledging the Authors Behind the AI Review Series[00:04:00] What Is Generative AI and Why Is It a Game-Changer?[00:06:00] The Cambrian Explosion of Generative AI in Medicine[00:08:00] Understanding Transformer Architectures and Cloud Computing[00:12:00] ChatGPT, DALLE, and Multi-Modal AI: What’s Next?[00:18:00] Synthetic Data Generation: A New Era for Pathology Training[00:24:00] How AI Can Pass Medical Exams and Assist Pathologists[00:30:00] Reducing Bias and Ethical Concerns in AI-Based Diagnostics[00:38:00] Real-World Use Cases of AI-Generated Pathology Reports[00:45:00] The Future of Generative AI in Digital Pathology🩺 Why This Episode Matters:
Generative AI is no longer just a concept—it’s already being used to train models, generate high-fidelity pathology images, and assist with diagnostic decision-making. However, challenges remain, from bias in AI models to the need for domain-specific training data. Understanding these factors is essential for pathologists and medical professionals who want to leverage AI responsibly in clinical practice.🚀 What’s Next?
This episode discusses not just what Generative AI is but how it can reshape pathology workflows and where we’re headed next. If you’re interested in how AI can improve efficiency and accuracy in diagnostics, this is a conversation you don’t want to miss.🎧 Listen now to explore the future of Generative AI in pathology!
👉 Watch or listen here: https://www.youtube.com/live/hRv9GmMWSjk?si=OEg8gafqRA2M_zlx
#DigitalPathology #AIinHealthcare #PathologyInnovation #GenerativeAI
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In this episode of the Digital Pathology Podcast, I explore the evolving role of Generative vs. Non-Generative AI in Medical Diagnostics. As AI continues to transform the medical field, understanding the differences between these two approaches is essential for pathologists, researchers, and healthcare professionals.
We break down the key concepts behind generative AI models (like ChatGPT and image-generation tools) and non-generative AI models (such as traditional machine learning for diagnostic support). I also highlight a groundbreaking seven-part AI review series published in Modern Pathology, which serves as a crucial reference for integrating AI into pathology.
🔬 Key Topics Covered:
[00:00:00] Introduction and Technical Adjustments[00:02:00] Why AI Education in Pathology Is More Important Than Ever[00:04:00] Overview of the Modern Pathology AI Review Series[00:06:00] Generative vs. Non-Generative AI: What’s the Difference?[00:08:00] AI in Pathology: Current Applications and Future Potential[00:12:00] Addressing Bias and Ethical Concerns in AI Models[00:16:00] How AI Can Improve Accuracy in Medical Imaging[00:20:00] The Role of Large Language Models (LLMs) in Pathology[00:25:00] Multi-Modal AI: The Future of Integrating Imaging and Text Data[00:30:00] Real-World Use Cases and AI-Driven Diagnostics🩺 Why This Episode Matters:
AI is no longer a futuristic concept—it’s here, and it’s shaping the future of digital pathology and medical diagnostics. In this episode, I break down how AI can enhance accuracy, improve workflow efficiency, and make diagnostic insights more accessible. However, AI models also come with risks, such as bias and interpretability challenges, which we need to address responsibly.🚀 Take Action:
AI in pathology isn’t just a passing trend—it’s a paradigm shift. Whether you're a pathologist, researcher, or lab professional, this episode will give you the knowledge you need to stay ahead in the era of AI-driven diagnostics.🎧 Listen now and explore the future of AI in pathology!
👉 Watch it here: https://www.youtube.com/live/Mq4Xwxoq_ok?si=o7bA90BlZff9iI_A
#DigitalPathology #AIinHealthcare #PathologyInnovation #GenerativeAI
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Welcome to the 21st edition of DigiPath Digest!
In this episode, together with Dr. Aleksandra Zuraw you will review the latest digital pathology abstracts and gain insights into emerging trends in the field.
Discover the promising results of the PSMA PET study for prostate cancer imaging, explore the collaborative open-source platform HistioColAI for enhancing histology image annotation, and learn about AI's role in improving breast cancer detection.
Dive into topics such as the role of AI in renal histology classification, the innovative TrueCam framework for trustworthy AI in pathology, and the latest advancements in digital tools like QuPath for nephropathology.
Stay tuned to elevate your digital pathology game with cutting-edge research and practical applications.00:00 Introduction to DigiPath Digest #21
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 PerplexityHistoColAI Github Page
01:22 PSMA PET in Prostate Cancer
06:49 HistoColAI: Collaborative Digital Histology
12:34 AI in Mammogram Analysis
17:21 Blood-Brain Barrier Organoids for Drug Testing
22:02 Trustworthy AI in Lung Cancer Diagnosis
30:09 QuPath for Nephropathology
35:30 AI Predicts Endocrine Response in Breast Cancer
40:04 Comprehensive Classification of Renal Histologic Types
45:02 Conclusion and Viewer Engagement
Links and Resources:
Publications Discussed Today:
📰 Can PSMA PET detect intratumour heterogeneity in histological PSMA expression of primary prostate cancer? Analysis of [68Ga]Ga-PSMA-11 and [18F]PSMA-1007📰 HistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration
📰 Advanced tissue technologies of blood-brain barrier organoids as high throughput toxicity readouts in drug development
📰 Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images
📰 GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning
📰 Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer
📰 Leveraging explainable AI and large-scale datasets for comprehensiv
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In this episode of the Digital Pathology Podcast, you will learn about cytology's entrance into the digital pathology space, including successful AI and scanner implementations.
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 Perplexity
We cover AI's role in rapid on-site evaluation for lung cancer and share insights on a looming prostate cancer surge and how digital pathology and AI can help. I
You will also listen to a live demo of me using an AI assistant to decode a scientific paper in real-time. Tune in to stay on top of the digital pathology research in 2025!
00:00 Welcome to DigiPath Digest
00:53 Introduction and New Year Greetings
01:41 Diving into DigiPath Digest
01:44 AI in Respiratory Cytology
06:11 The Role of AI in Pathology
09:49 Multi-Omics and AI
11:28 Radiomics and Pathomics
14:44 Live Q&A and Future Plans
20:09 Prostate Cancer Tsunami
22:34 Thyroid Cytology and Live AI-Assistant demo
31:07 Conclusion and the option to send texts :)
Links and Resources:
Publications Discussed Today:
📝 Evaluation of an enhanced ResNet-18 classification model for rapid On-site diagnosis in respiratory cytology
📝 Advancing precision medicine: the transformative role of artificial intelligence in immunogenomics, radiomics, and pathomics for biomarker discovery and immunotherapy optimization
📝 A machine learning approach to predict HPV positivity of oropharyngeal squamous cell carcinoma
📝 The uropathologist of the future: getting ready with intelligence for the prostate cancer tsunami
📝 Artificial Intelligence and Whole Slide Imaging Assist in Thyroid Indeterminate Cytology: A Systematic ReviewSupport the show
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In this episode, I’m joined by Dr. Giovanni Lujan, Nick Best, and Dr. Alae Kawam to explore a topic that hits close to home for many of us in digital pathology: why do so few pathologists attend digital pathology conferences? We delve into the barriers, opportunities, and actionable solutions that can help bridge this gap and drive the adoption of digital pathology across the profession.
What You’ll Hear in This Episode:
Startling Observations (00:02:00): Only 10% of attendees at some digital pathology conferences are pathologists. Why is this the case, and what does it mean for the future of the field?Barriers to Adoption (00:04:00): From time constraints to a lack of institutional support, we unpack the key challenges stopping pathologists from going digital.Mentorship and Collaboration (00:09:00): How mentorship programs can connect seasoned professionals with early-career pathologists to share knowledge and drive adoption.The Role of the Next Generation (00:15:00): Insights into how young pathologists can lead the way with their enthusiasm and fresh perspectives.Engaging the Skeptics (00:07:00): Strategies to introduce hesitant or resistant pathologists to the transformative power of digital tools.Global Comparisons (00:10:00): What can the U.S. learn from Europe and Asia about accelerating digital pathology adoption?Leveraging Leadership and Advocacy (00:19:00): How young pathologists can work with leadership to introduce digital pathology as a standard practice in their organizations.The Impact of Digital Pathology on Work-Life Balance (00:20:00): Exploring how remote sign-outs and shorter turnaround times can enhance both patient care and pathologists’ quality of life.Making Digital Pathology the Norm (00:24:00): Ideas for shifting digital pathology from a secondary option to the standard of care, addressing common fears and misconceptions.Future Plans and Next Steps (00:28:00): A look at actionable steps for advancing digital pathology through podcasts, mentorship, and departmental advocacy.Key Takeaways:
This conversation isn’t just about identifying challenges—it’s about solutions. We discuss how collaboration, leadership, and individual responsibility can drive meaningful change in digital pathology. Whether you’re a seasoned pathologist or just starting your career, this episode offers inspiration and actionable ideas to make digital pathology a core part of the profession.Connect With Us:
Share your thoughts on why more pathologists aren’t attending these conferences. What’s holding them back, and what changes would you like to see in your department? Let’s keep this important conversation going!Support the show
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Leveraging AI for Deep Insights into Tertiary Lymphoid Structures in Colorectal Cancer
116: DigiPath Digest #18 | Federated Learning in Pathology. Developing AI Models While Preserving Privacy
In 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 Introduction
00:45 Introducing the New AI Tool: Notebook LM by Google
01:11 Experimental Series: "Aleks + AI"
02:06 Deep Dive into Tertiary Lymphoid Structures (TLS)
03:18 Understanding TLS and Their Role in Colorectal Cancer
04:20 Quantification Methods and Key Findings
05:02 Implications for Personalized Medicine
09:02 AI in TLS Analysis and Future Prospects
11:00 CMS Classification and TLS Density
12:08 Study Limitations and Future Directions
15:40 Final Thoughts and Wrap-Up
16:28 Feedback and Future Plans
THIS EPISODE'S RESOURCESPUBLICATION 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
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In today's DigiPath Digest, we delve into federated learning, a decentralized approach to AI training that preserves data privacy.
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 Perplexity
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 Greetings
00:18 Today's Topic: Federated Learning
00:57 AI Tools and Updates
04:39 Federated Learning in Detail
08:03 Challenges and Benefits of Federated Learning
11:21 Exploring More Papers and Future Plans
22:53 Wrapping Up and Final Thoughts
Links and Resources:
Publications 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/
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This 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.
[00:00:00] Challenges in Pathology Today
What You’ll Learn in This Episode:
Discussing the pathologist shortage, delayed diagnoses, and how AI can address these issues.[00:03:00] A Pathologist’s Dual Perspective
Dr. 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 Pathology
Insights into how clinician-centric AI tools like Aiforia are designed to improve diagnostic workflows and outcomes.[00:14:00] Addressing Challenges in AI Integration
Strategies for overcoming hurdles like algorithm aversion, skill retention, and fostering trust in AI systems.[00:22:00] Preparing Future Pathologists
The importance of incorporating AI training into residency programs and creating a digitally savvy workforce.[00:44:00] How to Implement AI Effectively
Practical advice on selecting tools, collaborating with providers, and setting realistic goals for AI adoption in practice.
Learn More About Aiforia: https://www.aiforia.com/Download Digital Pathology 101Contact Dr. Richard Doughty: [email protected] more videos created together with Aiforia: VIDEO PLAYLIST
Resources and Links Mentioned:
This episode is supported by Aiforia Technologies, leaders in AI-powered solutions for digital pathology.Do you know someone who should listen to this episode?
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In 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 Kottler
Dr. 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 AI
Nina 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 Orchestration
We 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 Radiology
Nina 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 Healthcare
We 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 Healthcare
We 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 Accuracy
Nina 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 Impact
We 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 Models
Combining 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 AI
We 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 Work
Nina 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!
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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.
Timestamps:
[0:00] PathVision Highlights & Global Attendees[5:15] AI in Diagnostic Workflows: Dr. Anil Parwani’s “Pathology Train Ride”[12:30] Moving Beyond Narrow AI: Multimodal and Foundational Models[18:45] Glassless Pathology: A New Frontier with MUSE Microscopy[25:10] Integrating Digital Microscopy in Global Health Labs[32:00] Breast Cancer Month: New Advances in AI for Diagnostics[42:00] One Health & AI for Disease Detection in Primary Care[48:30] Special Interviews: Jun Fukuoka and Asian Society of Digital PathologyLinks and Resources:
Subscribe to Digital Pathology Podcast on YouTubePathology News Signify Research Monthly RecapYouTube version of this episodePublications 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/
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In this episode, I meet with Adam Cole, MD, and Jason Camilletti about how digital pathology transforms the field. Adam, the CEO of TruCore Pathology, and Jason, the CEO of PathNet Labs, share their unique journeys from the military to becoming digital pathology leaders. We explore their experiences, challenges, and innovations in integrating AI and digital tools into their practices.
Key Topics Discussed:
[00:00:00] Introduction to AI in Pathology[00:01:00] Adam and Jason’s Military Backgrounds[00:05:00] Adam’s Story of Becoming a Mobile Pathologist[00:10:00] The Move to Fully Digital Pathology[00:14:30] AI’s Role in Pathology[00:20:00] Challenges in Implementing Digital Pathology[00:25:00] Improving Patient Outcomes with Digital Tools[00:29:00] Digital Pathology’s Impact on Patient Care[00:38:00] Using AI for Quantifying Tumor Volume[00:40:00] The Role of AI in Enhancing Diagnostics
Adam and Jason emphasize the immense potential of AI in pathology, but also the need for thoughtful integration. The future of pathology lies in using digital tools to provide faster, more accurate diagnoses while maintaining the critical human element. Tune in to learn how AI is reshaping the field and what it means for both pathologists and patients.
TruCore websitePathNet Website
THIS EPISODE'S RESOURCES:
The Evolution of Digital Pathology – from Improved Histology Quality to Fair Use of Pathology Data w/ Matthew O. Leavitt, DDx FoundationAchieving work-life balance in medicine as a pathologist with digital pathology w/ Todd Randolph, MD
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What does the FDA jurisdiction for LDTs mean for the labs? Do they need to worry? How do they need to change the way they operate?
In this episode, I talk with Dr. Thomas Nifong, a clinical pathologist and VP of CDX operations at Acrovan Therapeutics, about the recent FDA ruling on laboratory-developed tests (LDTs) issued on May 6th, 2024. We discuss the implications of considering LDTs as medical devices, requiring regulation, and explore the authority of FDA versus CLIA. The conversation also covers historical contexts, practical implications of regulatory changes, and the roles of organizations like CAP, ACLA, and AMP in legal challenges against the FDA. We dive into the differences in requirements between CLIA and FDA, New York's alternative approval route, and potential impacts on lab operations and compliance. Join us for an insightful conversation filled with essential information for those in the field of molecular pathology.
00:00 Introduction and Special Guest Announcement
00:24 FDA's New Rule on Laboratory Developed Tests (LDTs)
01:58 Recording the Podcast: A Casual Lunch Conversation
03:47 Understanding FDA's Authority Over Medical Devices
08:07 Disputes and Legal Challenges
12:03 Practical Implications and Industry Reactions
12:47 Understanding FDA's Focus: Safety and Efficacy
14:11 The Role of CMS and Medical Necessity
14:48 Congressional Involvement and Legal Authority
16:06 Impact on Labs and Future LDTs
18:33 Quality Systems and Compliance
20:16 Modifications and Software Updates
21:16 Conclusion and Next StepsSupport the show
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In this episode, I had a fascinating conversation with Candice Chu, DVM, PhD, DACVP, about how artificial intelligence (AI) is reshaping veterinary diagnostics and education. Candice, a clinical pathologist and educator at Texas A&M, is using AI tools like ChatGPT to improve efficiency in clinical workflows and academic processes. We explored the practical applications of AI, ethical concerns, and its future impact on veterinary medicine.
[00:00:00] Introduction to AI in Veterinary Education and Diagnostics
Key Topics Discussed:
I ask Candice how AI is changing veterinary education and diagnostics, and she explains how AI is boosting efficiency in both areas.[00:01:00] Candice’s Journey in Veterinary Medicine
Candice shares her journey from Taiwan to the U.S., her career in veterinary pathology, and becoming an educator at Texas A&M.[00:05:00] Custom GPT Model for Clinical Pathology
Candice describes the development of her custom GPT model for clinical pathology and its role in improving diagnostic efficiency.[00:10:00] AI Tools for Academic and Clinical Efficiency
We talk about how AI tools reduce repetitive tasks, giving professionals more time for critical thinking and decision-making.[00:14:30] Ethical Concerns When Using AI in Veterinary Medicine
Candice emphasizes the ethical responsibility of using AI, highlighting the importance of human judgment in AI-assisted diagnostics.[00:20:00] How Veterinary Students Can Leverage AI
Candice shares tips on how students can use AI to enhance learning, from simplifying research to generating case questions.[00:29:00] AI’s Role in Academic Writing and Veterinary Practice
We discuss how AI tools streamline academic writing and research, and how AI will continue shaping veterinary practice in the future.[00:39:00] Critical Thinking and AI in Veterinary Medicine
Candice and I conclude by discussing how critical thinking and professional responsibility are essential when using AI tools.Candice highlighted the transformative role AI can play in both veterinary education and diagnostics, improving efficiency while requiring responsible use. While AI tools like ChatGPT offer many benefits, the human element—our critical thinking and judgment—remains crucial in ensuring accurate results and ethical practices.
This episode provides practical insights on how veterinary professionals, educators, and students can harness AI to streamline workflows and improve diagnostic accuracy. Be sure to listen to the full conversation for actionable tips on integrating AI into your practice!
About Dr. Candice Chu (Including her social media and achievements)Candice's PaperUndermind AIYoutube Episode of this Episode
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In this episode, Dr. Richard Fox shares how AI is transforming veterinary diagnostics. From his early career to the world of AI, Dr. Fox offers practical insights into the challenges, opportunities, and innovations that AI brings to pathology. Tune in to learn how AI is enhancing workflow efficiency, diagnostic precision, and the future direction of veterinary pathology.
[00:00] Introduction – Introduction to Dr. Richard Fox and his expertise in veterinary pathology and AI.
[03:00] Dr. Fox’s Career Journey – His shift from veterinary practice to pathology and AI.
[08:00] Entering the AI Space – How Dr. Fox became involved in AI, including his work with Aiforia.
[15:00] AI in Diagnostics – AI’s impact on diagnostic workflows and speeding up tasks.
[22:00] Quality Control in AI Models – Ensuring AI model accuracy and the importance of data consistency.
[28:00] AI Model Validation Challenges – Overcoming issues with model validation and retraining.
[35:00] Integrating AI into Workflows – How AI fits into veterinary pathology workflows and practical considerations.
[40:00] Future of AI in Pathology – Predictions on the future trends in AI and on-premises diagnostics.
[50:00] Common Questions About AI – Addressing concerns like AI replacing pathologists and optimizing workflows.
[58:00] Conclusion – Key takeaways and how to get started with AI in veterinary diagnostics.
The Episodes Resources:
Contact Aiforia
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In this 14th episode of DigiPath Digest, I introduce a new course on AI in pathology, designed to help pathologists understand and confidently navigate AI technologies.
The episode focuses on various research studies that highlight the integration and effectiveness of AI in pathology, particularly in colorectal biopsies and kidney transplant biopsies, emphasizing the importance of seamless workflow integration.
You will also learn about challenges in manual assessment of tumor-infiltrating lymphocytes and HER2 expression in breast cancer. I advocate for more consistent and precise AI-driven approaches.
And there an opportunity for a discounted beta test of the new AI course.
00:00 Welcome to DigiPath Digest #1400:24 New AI Course Announcement
01:51 Deep Learning in Colorectal Biopsies
09:17 AI in Kidney Biopsy Evaluation
16:12 Automated Scoring of Tumor Infiltrating Lymphocytes
24:22 AI for HER2 Expression in Breast Cancer
31:13 Conclusion and Course Details
THIS EPISODE'S RESOURCES
📰 A deep learning approach to case prioritisation of colorectal biopsies
🔗 https://pubmed.ncbi.nlm.nih.gov/39360579/
📰 Galileo-an Artificial Intelligence tool for evaluating pre-implantation kidney biopsies
🔗 https://pubmed.ncbi.nlm.nih.gov/39356416/
📰 Automated scoring methods for quantitative interpretation of Tumour infiltrating lymphocytes (TILs) in breast cancer: a systematic review
🔗 https://pubmed.ncbi.nlm.nih.gov/39350098/
📰 Precision HER2: a comprehensive AI system for accurate and consistent evaluation of HER2 expression in invasive breast Cancer
🔗 https://pubmed.ncbi.nlm.nih.gov/39350085/
▶️ YouTube Version of this Episode:
🔗 https://www.youtube.com/live/jkT8dTxelt4?si=xT6MNH7O4HuUnAN6
📕 Digital Pathology 101 E-book
🔗https://digitalpathology.club/digital-pathology-beginners-guide-notification
🤖 "Pathology's AI Makeover" Online Course 50% OFF
🔗 Let me know that you are interested in LinkedIn (just 10 spots available)Support the show
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Good morning, digital pathology trailblazers! Welcome to another exciting exploration of digital pathology and AI. I’m thrilled to have our global community here with us today from so many different time zones. Before we dive into today's content, a quick note: my equipment is being a bit finicky, but that’s life in the digital world!
Integrating Image Analysis with AI
Let's kick off with a recap of some recent updates. Yesterday, I had the privilege of presenting to a mixed group at Cincinnati Children’s Hospital. We discussed AI in image analysis, an essential tool bridging radiology and pathology as these fields rapidly evolve with new technologies like foundation models and large language models. A diverse audience—ranging from radiologists to pathologists—prompted me to adapt my presentation style on the spot. It was a dynamic discussion about the advancements in healthcare that shared perspectives from both sides.
Lymphovascular Invasion: A Case Study
Our first paper today focuses on a deep learning model for identifying lymphovascular invasion (LVI) in lung adenocarcinoma. This significant prognostic factor is crucial for advancing diagnostic consistency and reliability. Unlike broad foundation models, this work engages with dedicated image analysis applications targeting specific diagnostic challenges. The study demonstrated reduced pathologist evaluation time by nearly 17% and even more in complex cases, aligning with previous findings that AI enhances efficiency by around 21%.
AI Collaborations: Human and Veterinary Pathology
Next, we delve into a collaborative effort between human and veterinary pathologists, emphasizing the promise of AI integration in telepathology and digital pathology. These fields are converging to enhance information exchange, teaching, and research. I’m particularly excited about this paper due to my own veterinary pathology background and the potential it offers for both educational and clinical practices.
Spatial Profiling and Immuno-Oncology
We then journey into the intricate landscape of immuno-oncology with a study on PD-1 and PD-L1 in osteosarcoma microenvironments. Utilizing deep learning and multiplex fluorescence immunohistochemistry, researchers highlighted the spatial orchestration of these markers, providing insights into potential immunotherapeutic strategies. This work is an exemplar of how AI can illuminate complex biological landscapes, offering a path for future therapies.
Conclusion
Thank you all for joining this vibrant discussion. Whether you’re tuning in from early morning in Atlanta or late at night in Algeria, your engagement enriches our learning experience. Keep an eye out for more content and upcoming courses designed to unpack these groundbreaking developments in AI and digital pathology.
Until next time, keep blazing trails in digital pathology!
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The episode explores the concept of blind review, a process designed to eliminate hindsight bias by allowing medical experts to evaluate cases without knowing the outcome or the hiring party.
Stephanie's LinkedIn ProfileThe Blind Review Website
Stephanie Franckewitz, JD, MBA, founder of Blind Review, discusses its application in legal cases, particularly for digital pathology and radiology. By providing an unbiased expert opinion, blind review aids the defense and plaintiff parties in court, increasing the chances of a favorable verdict.
Stephanie outlines her journey from a medical malpractice defense lawyer to starting Blind Review and highlights the potential for digital pathology to revolutionize the legal process, reduce bias, and improve case outcomes.
Collaboration with platforms like PathPresenter enables pathology slides to be reviewed efficiently and effectively within a legal context. This approach benefits both defendants and plaintiffs by ensuring objective evaluations and enhancing the credibility of expert testimonies in trials.
00:00 Introduction to Blind Review
01:19 The Role of Digital Pathology in Legal Cases
02:16 Stephanie Franke Reid's Journey
07:19 Challenges in Traditional Expert Reviews
10:09 Implementing Blind Review in Pathology
18:16 Collaboration with PathPresenter
25:43 Streamlining the Legal Process with Digital Pathology
26:51 Collaborative Tools for Legal Experts
27:20 Path Presenter: A Game Changer for Attorneys
28:17 Understanding Pathology for Juries
29:20 Streamlining Case Preparation with Path Presenter
31:54 Setting Up a Blind Review Process
35:38 The Gold Standard of Blind Review
41:53 Impact of Blind Review on Legal Outcomes
49:49 Empowering Legal and Medical Professionals
54:50 Conclusion and Call to Action - contact Stephanie
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In this episode, I celebrate another milestone of the Digital Pathology Place YouTube channel that was achieved thanks to you, my digital pathology trailblazer, reflecting on its journey since its inception in 2019.
The YouTube version of "AI in Pathology" first videoThe updated "Artificial Intelligence in Pathology" video (coming soon in podcast version)
I delve into the developments in digital pathology, focusing on the first video I ever published on YouTube about AI in pathology, highlighting trends, tools, and challenges in the field.
The video was based on a presentation I gave on the day I got engaged, so if you want to know the whole story listen in.
I explain key concepts like
- artificial intelligence,
- machine learning, and
- deep learning, and discuss
- How could AI eventually support pathology practice despite current challenges?
00:00 Welcome and AI Co-Host Feedback
00:19 YouTube Monetization Milestone
01:18 Reflecting on the First Video
02:47 Special Day and Personal Story
05:06 Introduction to AI in Pathology
07:26 AI Terminology and Concepts
13:17 Current Status of AI in Pathology
17:33 Challenges and Future of AI in Pathology
22:42 Conclusion and Call to Action
23:30 Updates and Future Plans
THIS EPISODE'S RESOURCESSupport the show
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- Visa fler
