State-Of-The-Art Medical Data De-identification and Obfuscation
This event qualifies for 1 CPEs
The process of de-identifying protected health information (PHI) from unstructured medical notes is often essential when working with patient-level documents, such as physician notes. Using current state-of-the-art techniques, automated de-identification of both structured and free-text medical text can be accomplished at the same level of accuracy as with human experts.
Recently, John Snow Labs’ Healthcare Natural Language Processing (NLP) library – the most widely used such tool in the healthcare and life science industries – has achieved new state-of-the-art accuracy on standardized benchmarks. This webinar will introduce this solution and compare its accuracy, speed, and scalability to human efforts and to the three major cloud providers.
Join us for this webinar, where we will delve into practical implementation details and scenarios. Attendees will:
- Understand text de-identification in various human languages
- Discuss data obfuscation techniques
- Review the recommended setup for industrial-strength deployment
Speaker and Presenter Information
Jiri Dober, Head of Solutions, John Snow Labs
Luca Martial, Data Scientist, John Snow Labs
Relevant Government Agencies
Dept of Health & Human Services, Other Federal Agencies, Federal Government, State & Local Government
Event Type
Webcast
This event has no exhibitor/sponsor opportunities
When
Thu, Feb 23, 2023, 2:00pm - 3:00pm
ET
Cost
Complimentary: $ 0.00
Website
Click here to visit event website
Event Sponsors
Organizer
John Snow Labs Government Team at Carahsoft