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De-Identification Blog

Methods, Tools, and Best Practices for Automated Data De-identification.

Accurate Medical Data De-identification with John Snow Labs’ De-identification Service

Modern-day wise folks say that “data is the new oil”. Data supports cutting-edge research, drives innovation, and helps with the development of solutions to real-world problems. This is especially true...

Lessons Learned De-Identifying 700 Million Patient Notes with Spark NLP

Providence St. Joseph Health’s (PSJH) unstructured data de-identification methodology relies on pre-trained BiLSTM-CNN-Char NER models provided by John Snow Labs. The PSJH Data science department evaluated John Snow Labs models...

Using Spark NLP to De-Identify Doctor Notes in the German Language

The ability to extract clinical information at large scale and in real time from unstructured clinical notes is becoming a mission critical capability for IQVIA. Key data elements like tumor...

Automation of Data De-identification

Introduction With evermore personal data being produced and stored by organizations, data privacy is becoming an increasing priority. Businesses have access to a lot of sensitive information about their customers,...

Simpler & More Accurate Deidentification in Spark NLP for Healthcare

Spark NLP for Healthcare 3.1 improves the accuracy, functionality, and ease of use of the library’s data de-identification capabilities. All improvements come directly from customer feedback, as the library is...