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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 discuss:

Why pathologists and computer scientists are often lost in translation
How AI bias, regulation, and ethics are being addressed — globally
What it really takes to operationalize AI in patient care today

If you’ve ever asked, “Where do I even start with AI in pathology?” — this is your answer.

🔍 Highlights & Timestamps
00:00 – The importance of earned trust in AI
01:00 – Education gaps in AI for both pathologists & developers
03:00 – Why CPAiCE was built & the three missions it serves
07:00 – The seven-part series: a blueprint for AI literacy
10:00 – Making AI education accessible without losing technical integrity
13:00 – How this series is being used for global teaching (including by me!)
17:00 – Generative AI in creating figures vs. human-authored content
21:00 – Eye-opening global AI regulations that pathologists MUST know
24:00 – Ethics, bias & strategies to mitigate real clinical risks
30:00 – What’s next: CPAiCE’s mission to reshape pathology education & practice
34:00 – A teaser: the first CPAiCE textbook is on the way!

📚 Resources from This Episode
📰 Read the full series (open access!):
Modern Pathology 7-Part AI Series: https://www.modernpathology.org/article/S0893-3952(25)00001-8/fulltext

👨‍⚕️ UPMC’s Computational Pathology & AI Center of Excellence (CPAiCE)
🌍 Creative Commons licensing means YOU can reuse, remix & teach from these resources — just cite the source.

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Chapters

1. Ethics as Core to AI Development (00:00:00)

2. Creating the Computational Pathology Center (00:03:51)

3. Bridging Knowledge Gaps Through Education (00:04:21)

4. The Birth of a Seven-Part AI Series (00:06:20)

5. Making AI Knowledge Accessible (00:09:21)

6. Ethics and Bias in AI Systems (00:16:53)

7. The Future of Computational Pathology (00:19:53)

8. Closing Remarks and Takeaways (00:38:00)

167 episodes

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