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

This event has no exhibitor/sponsor opportunities

Thu, Feb 23, 2023, 2:00pm - 3:00pm ET

Complimentary:    $ 0.00

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Event Sponsors

John Snow Labs

John Snow Labs Government Team at Carahsoft

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