How Limina Is Making Sensitive Health Data Safe for AI

About this episode

This episode features a discussion on the challenges of privacy in healthcare AI with Patricia Thaine from Limina.

In this episode, host Sandy Vance sits down with Patricia Thaine, co-founder and chair of Limina (formerly known as Private AI), for a fascinating conversation about one of the most underappreciated bottlenecks in healthcare AI adoption: the privacy of unstructured data. With a background in natural language processing and privacy research, Patricia built the company from the ground up to solve a problem most organizations did not even know they had. Today, her platform helps health systems, research organizations, and payers de-identify everything from clinical notes to ambient listening data so they can train models, share data for research, and move their AI initiatives forward without putting patient privacy at risk. If your AI initiative is stalled because of privacy concerns, this episode is exactly what you need to hear.

People in this episode

Host: Sandy Vance

Guest: Patricia Thaine

Topics covered

• healthcare AI
• data privacy
• unstructured data
• de-identification
• machine learning
• patient privacy

Keywords

• health data
• AI adoption
• privacy concerns
• clinical notes
• ambient listening data
• data sharing
• research organizations

Mentioned in this episode

Organizations: Limina, Private AI

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