ABOUT THIS PODCAST 🔗
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.
Hosts:
Update frequency:
every 10 days
Average audio length:
37 minutes
Guest interviews
English
United States
250 episodes
since Sept. 26, 2019
episodic
AUDIENCE OF THIS PODCAST 🔗
~65.21% of listeners are from Ireland.
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IE
65.21%
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US
17.08%
🇰🇪
KE
11.64%
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JP
2.63%
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XK
1.08%
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PH
0.46%
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NZ
0.46%
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UA
0.31%
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PE
0.15%
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TW
0.15%
🇳🇱
NL
0.15%
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IN
0.15%
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DE
0.15%
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DZ
0.15%
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UG
0.15%
Others
0.08%
* Data source: directly measured on Listen Notes. real-time
LATEST EPISODE 🔗
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Can you use AI to write scientific papers without fabricated references, journal trouble or learning to code? I recorded this episode at the airport on my way to ESTP 2026 in Kraków. It's my practice run of the talk I gave there.
When deep learning came into pathology, people …
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PREVIOUS EPISODES 🔗
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What happens when AI models that perform almost perfectly on scattered cervical cells become less reliable than a coin flip on crowded cell groups?
In DigiPath Digest #51, I examine what this performance gap tells us about artificial intelligence in cytopathology.
The first paper e…
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What good is a powerful foundation model if it slows the pathologist down, can’t explain its result, or doesn’t fit the clinical workflow?
Foundation models are gaining attention across digital pathology. But they’re not finished clinical tools by themselves.
In this episode of the…
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Does more experience automatically make a cytotechnologist more accurate—or does where they look first matter more?
In DigiPath Digest #50, I review a digital cytology eye-tracking study that challenges the assumption that diagnostic accuracy improves steadily with years of practic…
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Can a treatment decision depend on whether one pathologist sees 45% biomarker positivity and another sees 55%?
Visual immunohistochemistry scoring helped establish precision oncology. But as targeted therapies become more sensitive to subtle biological differences, categorical scor…
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Is your digital pathology rollout moving so slowly that it’s creating a fragmented workflow instead of transforming the department?
In this episode of the Digital Pathology Podcast, I speak with Dr. Syed Hoda, Director of Digital Pathology at NYU, about why gradual implementation m…
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If AI is already being used across the drug development pipeline, why hasn’t its impact matched the investment?
AI can help researchers review scientific literature, predict protein structures, prioritize molecules, assess toxicity, support clinical trials, and monitor adverse even…
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What does AI literacy actually look like for pathologists, researchers, and future clinicians? And how do you teach it in a way that is practical, not abstract?
In this episode, I talk with Candice Chu, DVM, PhD about something I think a lot of people in digital pathology and compu…
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Are pathology foundation models actually ready for labs, or are they still stronger on paper than in practice?
In this episode of DigiPath Digest #49, I unpack a timely review on pathology foundation models and ask the question that matters most to me: not just what these models ca…
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How far can pathologists take visual biomarker scoring before human vision becomes the bottleneck?
In this episode, I talk with Doug Bowman. PhD, VP Precision Medicine at Indica Labs, about what happens when companion diagnostics move from traditional visual scoring into the era of…
Disclaimer: The podcast and artwork embedded on this page are from Aleksandra Zuraw, DVM, PhD, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.
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