As AI and analytics initiatives accelerate across health systems, so too does the urgency to safely de-identify multimodal patient data. But while structured data de-identification is well-trodden ground, health systems are now tackling the rapidly-evolving challenge of de-identifying text, images, and other emerging data types.
Join this webinar to explore how leading organizations are expanding their understanding and approaches to broadening data types to enable innovation.
In this session, you’ll learn:
- Concepts of re-identification risk and mitigation applied across diverse data types
- Practical approaches to de-identify unstructured data, including clinical notes and medical images.
- Lessons from real-world customer examples of de-identification initiatives
%20-%20Somer%20Sinnard.jpg?width=120&height=120&name=headshot%20(1)%20-%20Somer%20Sinnard.jpg)