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De-Identification Blog

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

GLiNER and OpenPipe Shine on General Texts but Miss Over 50% of Clinical PHI — Compared to Less Than 5% Misses by Solutions Like John Snow Labs It’s often assumed...

Evolving from Knowledge to Reasoning in Healthcare AI John Snow Labs has been at the forefront of healthcare AI, consistently developing state-of-the-art language models specialized for the medical domain. Our...

De-identification is the process of removing or masking sensitive, personally identifiable information from data, particularly in medical records. This is crucial to protect patient privacy and comply with regulations like...

John Snow Labs' Medical Language Models library is an excellent choice for leveraging the power of large language models (LLM) and natural language processing (NLP) in Azure Fabric due to...