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What if climbing the digital pathology “mountain” isn’t about reaching the summit alone—but knowing where base camp is, and who you bring with you?

In this episode, I take you inside the Digital Diagnostic Summit in Park City, hosted by Lumea, where fewer than 100 digital pathology leaders gathered to share their journeys, challenges, and solutions. 

From resilient metaphors of Everest climbs to practical strategies for workflow ownership, clinical trials, and AI-powered biomarkers, this summit showed that the future of diagnostics is built on collabora...

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What if up to 35% of the diagnostic color data on your pathology slides never reaches your eyes—just because of your monitor? In this episode, sponsored by Barco, I sit down with Dr. Monika Lamba Saini (ADC Therapeutics) and Tom Kimpe (Barco) to uncover why color calibration in digital pathology isn’t optional anymore—it’s critical for diagnosis, efficiency, and AI readiness.

Highlights:

[00:03:42] Monika’s path from CROs to biopharma and why color consistency matters in clinical trials.[00:09:22] What “color science” means in pathology a...

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7 Counterintuitive Secrets from NCCN’s 2025 AI in Cancer Care Summit

When the National Comprehensive Cancer Network (NCCN) gathers healthcare leaders, people listen. I attended the 2025 Policy Summit on the evolving AI landscape in cancer care—and walked away with insights that were raw, practical, and surprisingly hopeful.

Instead of hype or overpromising, cancer care leaders shared honest strategies for implementing AI responsibly and effectively. In this episode, I break down the 7 counterintuitive secrets they’re using to fast-track adoption—while others remain stuck.

Whe...

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What if the way we quantify pathology is more guesswork than science? In this episode of DigiPath Digest, I take you through the latest research where AI is not just supporting but challenging traditional methods of image analysis in neuropathology, nephrology, hematology, and cytology. From Boston brain banks to Mayo Clinic kidney models, we look at how advanced AI compares to human vision—and where it already outperforms us.

Episode Highlights:

[00:02:49] Neuropathology image analysis (Boston VA & BU) – Why traditional semiquantitative scoring often fails, and how...

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What if the AI tools we trust for cancer diagnosis are not always correct? This episode of DigiPath Digest takes on the uncomfortable but critical question: can AI “lie” to us—and how do we verify its performance before adopting it in clinical practice?

Highlights:

[00:02:00] Foundation models in action: Deployment of a fine-tuned pathology foundation model for EGFR biomarker detection in lung cancer—reducing the need for rapid molecular tests by 43%.[00:08:41] Bone marrow AI misclassifications: Why automated digital morphology still struggles with consiste...

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What if AI could predict cancer outcomes better than traditional methods—and at a fraction of the cost? In this episode, I explore how multimodal AI is reshaping lung and prostate cancer predictions and why integration challenges still stand in the way.

Episode Highlights with Timestamps:

[00:02:57] Agentic AI in toxicologic pathology – what it is and how it could orchestrate workflows.[00:05:40] Grandium desktop scanners – making histology studies more accessible and efficient.[00:08:03] Clover framework – a cost-effective multimodal model combining vision + language for pathology.[00:13:40] NSCLC...

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How can pathology labs keep up with rising cancer diagnoses when the workforce is shrinking?  Dr. Anil Parwani believes the answer lies in digital pathology powered by AI—and in this episode, he shares how his team at Ohio State University is making it work today.

Amid increasing demands and workforce shortages, pathology is embracing digital transformation. The Ohio State University, for instance, has scanned over 4.2 million slides since 2016, leveraging digital pathology for standardization and objectivity. 

Current AI applications aid in biomarker quantification, rare event detection, and tumor classification, with...

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“AI in Pathology Isn’t Coming — It’s Already Here. Are You Ready?”

From confusion to clarity — that’s what this episode is all about. I sat down with Drs. Liron Pantanowitz, Hooman Rashidi, and Matthew Hanna to dissect one of the most important and comprehensive AI-in-pathology resources ever created: the 7-part Modern Pathology series from UPMC’s Computational Pathology & AI Center of Excellence (CPAiCE). This isn’t just another opinion piece — it's your complete guide to understanding, implementing, and navigating AI in pathology with real-world insights and a global lens.

Together, we di...

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Can AI Grade Cancer Better Than Us? The Truth About T-Cell Imaging, Biomarkers & Digital Pathology Disruption

You think Saturday mornings are for coffee? Try diving into bone marrow morphology, organ donor kidney biopsies, and AI-driven metastasis detection at sunrise. That’s how I do it—and you’re invited to join.

Welcome to another data-packed episode of DigiPath Digest, where we explore the latest frontier in digital pathology and AI. This time, I reviewed some of the most exciting recent abstracts spanning cancer...

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AI Pathology & Genomics: A New Benchmark for Predicting Gene Mutations

If you still think visual quantification is “good enough” in pathology, think again.
In this 27th episode of DigiPath Digest, I break down four transformative abstracts that show how AI is shifting our diagnostic landscape—from breast cancer segmentation to fibrosis assessment, and all the way to spatial immunology and the evolving immunoscore.

If you’re still relying on manual scoring, static staging systems, or single-marker immunohistochemistry, this episode will challenge you to look deeper—l...

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If our visual scoring is still based on gut feeling, how do we scale precision?
In this week’s DigiPath Digest, I explored four new AI-focused papers that could reshape how we diagnose prostate, bladder, gastroesophageal, and endocrine cancers.

From automated IHC scoring to predicting urethral recurrence post-cystectomy, these studies highlight the growing value—and responsibility—of integrating AI into our pathology workflows.

And yes, I also reveal where to get my histology-inspired earrings 😉

Episode Highlights

[06:00] Muse Vet Platform...

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If we don’t learn to work with LLMs now, we might end up competing with them. 🧠
In this week’s DigiPath Digest, I return to our Journal Club to unpack the latest research on AI in tumor classification, focusing on GPT-4o, LLaMA, and other LLMs. Can these models really outperform traditional tools when analyzing pathology reports?

Surprisingly—yes. But don’t panic. This episode is about understanding what LLMs actually bring to the table, how they’re being evaluated, and what we need...

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AI in Pathology: ML-Ops and the Future of Diagnostics

What if the most advanced AI models we’re building today are doomed to die in the machine learning graveyard? 🤯 That’s the haunting question I tackled in the final episode of our 7-part series exploring the Modern Pathology AI publications.

In this session, I explored machine learning operations (ML-Ops)—what they mean for digital pathology —and why even the most brilliant algorithm can fail without proper deployment strategies, data infrastructure, and lifecycle management.

But we don’...

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Can We Ever Eliminate Bias in AI for Pathology?

Every time we think we’ve trained a “neutral” algorithm, we discover our own fingerprints all over it. Our biases. Unconscious. Systemic. Data-driven. And if we ignore them, AI won’t just fail—it will fail patients.

Welcome back, my digital pathology trailblazers! In this sixth episode of our 7-part AI in Pathology series, we tackle one of the most uncomfortable yet necessary conversations: Ethics and Bias in AI and Machine Learning. These are...

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The Most Overlooked Risk in AI for Pathology? It’s Not What You Think…

Welcome, my trailblazing digital pathologists! In this episode, I dive headfirst into the regulatory maze of Artificial Intelligence (AI) in pathology, covering global frameworks, safety risks, ethics, and the future of software as a medical device. While regulation might not be the flashiest part of AI, ignoring it could cost us innovation—or worse, patient safety.

We’re on Part 5 of our 7-part AI in Pathology series, and this one’s vital for...

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In this episode sponsored by Epredia, Dr. Anil Parwani explores the transformative journey of digital pathology from basic slide scanning to AI-driven diagnostics. He shares real-world implementation experiences and demonstrates how these technologies are addressing critical challenges in pathology practice.

Pathology faces increasing demands amid workforce shortages and knowledge explosionDigital pathology provides standardization, objectivity, and automation beyond glass slidesOhio State University has scanned 4.2 million slides representing nearly 500,000 cases since 2016Current AI applications include biomarker quantification, rare event detection, and tumor classificationIntegration challenges remain the primary barrier to seamless adoption of...

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You might be using AI models in pathology without even knowing if they’re giving you reliable results.
 

Let that sink in for a second—because today, we’re fixing that.

In this episode, I walk you through the real statistics that power—and sometimes fail—AI in digital pathology. It's episode 4 of our AI series, and we’re demystifying the metrics behind both generative and non-generative AI. Why does this matter? Because accuracy isn't enough. And not every model metric tells you the whole...

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What if I told you the biggest AI breakthroughs in pathology aren’t coming from ChatGPT or generative tools—but from the quiet power of predictive analytics and machine learning?

In this episode, I explore the non-generative side of artificial intelligence in pathology. These are the tools that detect tumors, segment tissue, classify images, and make predictions—without generating a single word.

It’s the third chapter in our guided AI series, and this time we focus on the models you’re more likely to use in real-world...

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❗️Is synthetic data trustworthy enough to train AI for patient care? It just might be—and that's what both excites and terrifies me. ❗️

Hey trailblazers! In this episode of the Digital Pathology Podcast, I take you through the second part of our AI in Pathology series—this time, we’re focusing on generative AI and how it’s revolutionizing diagnostics, education, and workflow in our field.

From synthetic H&E slides that could pass for real to multimodal agents that can read your histology images...

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Generative vs. Non-Generative AI in Pathology: Why the Difference Matters

If we don’t start defining what kind of AI we’re talking about, we risk letting buzzwords replace real science. 🧠
This is where we begin—at the foundation.

Welcome to the first episode of our 7-part Guided Journey through AI in Pathology, inspired by two must-read articles from Modern Pathology that you’ll want bookmarked forever (links below 👇).

In this episode, I clarify one of the most misunderstood distinctions in artificial...

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Will FDA rules disrupt the way we diagnose diseases? 

In this episode, I break down a seismic shift in lab medicine: a federal court has vacated the FDA’s controversial rule classifying lab-developed tests (LDTs) as medical devices. This change carries serious implications for innovation, digital pathology, AI-based diagnostics, and small labs across the U.S.

🎧 What You’ll Hear:

What LDTs are and why they matter for rare diseases and personalized medicine


Why the FDA rule sparked backlash from the pathology community

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You think going digital in pathology just means buying a scanner? 

Think again. 

In this episode sponsored by Epredia, I sat down with Ryan Davis, Director of Global Business Strategy at Epredia, to talk about what it really takes to implement digital pathology—and why modularity, cytology support, and AI integration are changing the game. 

Whether you’re starting your digital journey or scaling up with advanced tech, there’s something in this conversation for you.

🎯 Highlights with Timestamps:

[00:01:00] Who is Ryan Davis? Epredia’s digital tran...

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In this episode, I talk with Tiffany Chen, MD, and Ben Cahoon from Techcyte about Fusion, their new digital pathology platform. Fusion integrates clinical and anatomic pathology workflows, AI algorithms, and electronic health records—all into one streamlined experience.

We explore how Fusion simplifies case management, improves diagnostic accuracy, and brings AI-powered pathology into routine practice. Plus, we discuss the importance of open standards, partnerships with Mayo Clinic, and why flexible integration is key for healthcare innovation.

If you’re passionate about digital pathology, AI, and advancing patient care, this...

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Why do so many digital pathology tools stall before they ever reach patients? 

In this USCAP 2025 special sponsored by Muse Microscopy, I talk with Esther Abels, founder of SolarisRTC, regulatory strategist, and the force behind the first FDA-cleared whole slide imaging system.

We break down what startups and established companies must do from day one to succeedbin getting their devices through the FDA. Hint: regulatory strategy isn’t a final step—it’s your starting line.

🧠 What You’ll Learn: