Navigating Privacy in Unstructured Text: Advanced AI Solutions for Compliance and Data Insight

In today’s healthcare data landscape, unstructured text represents both a tremendous opportunity and a significant challenge. Unstructured text—such as free-text fields, clinical notes, and reports—comprises up to 80% of the world’s health data. While it is rich with clinical insights, the presence of patient identifiers introduces high privacy risks, requiring advanced solutions to ensure compliance.

This resource explores how cutting-edge AI solutions, including redaction and obfuscation techniques, can help organizations de-identify unstructured text, unlocking its full potential for analysis and downstream use cases. Discover how achieving HIPAA-compliant de-identification through methods like Expert Determination enables Life Sciences and healthcare teams to:

- Preserve data utility while maintaining privacy
- Reduce privacy risks in large-scale datasets
- Leverage unstructured data for clinical research and model training

Learn how AI-powered models and privacy experts ensure over 99% accuracy in identifying and protecting sensitive information, paving the way for safe and effective use of unstructured text data.