What Digital Pathology Means

This episode of Inference is dedicated to Breast Cancer Awareness Month. I’m talking with Akash Parvatikar – AI scientist and product leader in digital pathology and computational biology. He leads PathologyMap™ at HistoWiz, a digital pathology platform that turns whole-slide images into searchable, analyzable data with AI tools – streamlining research and accelerating insights for cancer and precision medicine.

Digital pathology is a very new field, but an important one, considering that the US is facing a large shortage of pathologists.

*What you’ll learn:*

- What “digital pathology” actually is – and why scanning glass slides changes everything

- Where AI already helps today and where it’s still just a very promising technology

- Why explainability, failure modes, and data standards decide clinical adoption

- What is the real bottleneck for using AI in pathology and diagnosis

- How agentic workflows might enter the lab in pieces first

- A practical timeline for digitization, FDA-type approvals, and hospital rollouts

- The human role that stays

*Big idea:* Digitize first. Validate carefully. Then scale tools that clinicians trust. Telepathology expands access. Good AI here speaks the pathologist’s language. Remember – AI that can’t explain itself in clinical terms won’t ship.

Watch the episode!

*Did you like the episode? You know the drill:*

 📌 Subscribe for more conversations with the builders shaping real-world AI.

 💬 Leave a comment if this resonated.

 👍 Like it if you liked it.

 🫶 Thank you for watching and sharing!

*Guest:* Akash Parvatikar, AI Scientist, leading PathologyMap at HistoWiz

https://www.linkedin.com/in/akash007/

https://home.histowiz.com/pathology_map/

📰 Want the transcript and edited version?

 Subscribe to Turing Post https://www.turingpost.com/subscribe

*Chapters:*

1:22 - The Current State and Future of AI in Cancer Diagnostics

2:27 - Real-World vs. Aspirational AI Breakthroughs in Patient Outcomes

3:36 - Evolution of AI Usage by Clinicians

4:47 - The Technical Challenges of AI in Pathology

7:22 - The Role of Generative AI in Diagnostics

8:42 - The Potential of Agentic AI Workflows in Pathology

9:50 - Key Bottlenecks in AI for Pathology

12:13 - About the Pathology Map Platform

13:49 - Navigating Regulations in AI-Powered Diagnostics

14:40 - The Human Impact of AI in Cancer Diagnostics

16:40 - What is Digital Pathology?

18:21 - Timeline for Mainstream Adoption of AI in Pathology

19:42 - The "Spotify for Precision Medicine"

20:20 - The Future Role of Humans in AI-Assisted Pathology

21:36 - The Economics of AI in Pathology

22:48 - Concerns and Excitations About the Future of AI in Pathology

24:43 - Book Recommendation

Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live.

*Sign up:* Turing Post: https://www.turingpost.com

Follow us:

Ksenia and Turing Post:

https://x.com/TheTuringPost

https://www.linkedin.com/in/ksenia-se

https://huggingface.co/Kseniase

#DigitalPathology #AIMedicine #CancerDiagnostics #PrecisionMedicine #BreastCancerAwareness #EarlyDetection #AIForGood