Where should a hospital’s AI actually run, and who controls the data it learns from?

In this episode of AI Meets MedTech, Anna Nesterova sits down in the studio with Samantha Rubinchik, CFO & Co-Founder of Warp Lab, to talk about the fight over data sovereignty in healthcare. Cloud AI promises speed and scale. But for many clinics and health systems, sending patient data off-site is a risk they won’t take. Samantha explains why on-prem infrastructure still matters, what “keeping data off the cloud entirely” means in practice, and what it takes for a hospital to trust an AI that runs on its own hardware. She even brought one of Warp Lab’s on-prem units into the studio.

We cover:

• Data sovereignty: who owns, controls and is accountable for patient data
• On-prem vs cloud AI: the real trade-offs in safety, cost and control
• Why some healthcare organizations keep patient data off the cloud completely
• What it takes to get a clinic or hospital comfortable with a local AI
• The business side: risk, liability and the economics of owning your AI stack

If you’re a healthcare leader, a MedTech founder, or anyone deciding where your organization’s AI should live, this one’s for you.

⏱️ Chapters

🔗 Links
Warp Lab: https://warp-lab.ai
Samantha Rubinchik on LinkedIn: [add link]
Newsletter & more: http://www.aimeetsmedtech.com/

🎧 Listen on Spotify, Apple Podcasts, Amazon Music and YouTube
Spotify: https://open.spotify.com/show/033v5JDoHlCbQsHWqV6YKA
Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-meets-medtech/id1896898150

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#HealthcareAI #MedTech #DataSovereignty #OnPremAI #CloudComputing #HealthIT #PatientData #AIinHealthcare #DigitalHealth

What if the device that digitizes your cancer biopsy cost under $5,000 instead of $200,000? In this episode of _AI Meets MedTech_, host Anna Nesterova talks with Michael, a UCLA PhD researcher and founder, about the portable AI-enhanced microscope scanner he built for pathology.They cover:

• Why most biopsies still aren't digitized, and why that holds back AI in pathology
  
• How continuous scanning with deep learning replaces expensive scanner mechanics
  
• A live demo of a cloud portal for remote, shared slide review
  
• What this could mean for rapid on-site evaluation, surgical margins and faster results for patients
  
• Whether AI will replace pathologists, and why Michael says no
  
• A blitz round on startups, microscopes and what AI will never replace
  

The device is currently research use only. Find Michael at scanamus.ai and on LinkedIn.

Chapters

• 00:00 Introduction to AI in MedTech
  
• 00:48 Michael Fanus's Journey and Motivation
  
• 04:04 The Unique Microscope Technology
  
• 09:57 Challenges in Pathology and Digitization
  
• 16:04 Real-Time Scanning and Pathologist Interaction
  
• 21:55 Future of Pathology and AI Integration
  
• 27:55 Vision for Patient Diagnosis and Treatment
  
• 33:55 Final Thoughts on AI and Pathology

In this episode of AI Meets MedTech, Urs Anliker discusses the evolving landscape of AI in healthcare, particularly focusing on digital biomarkers and their potential to transform patient care. He emphasizes the importance of collaboration between technology developers and healthcare professionals to create meaningful value in AI applications.

We also discussed the MedTech Meets AI Conference in Barcelona.

Chapters

• 00:00 AI in MedTech: A New Era
• 04:28 Digital Biomarkers: Transforming Healthcare
• 10:45 AI's Role in Home Healthcare Devices
• 14:39 Challenges and Opportunities in AI Development
• 18:28 Successful Implementations of AI in Healthcare
• 22:16 Collaboration for Value Creation in AI