Built-in HIPAA audit logging is now in Generative AI Lab 7.8. Track user actions, data access, and API activity with full PHI traceability out of the box.
Every healthcare AI team eventually faces the same uncomfortable question: Can you prove who accessed what, when, and why? Most can’t. Not cleanly. Not instantly. Not in the way a...
This post presents a comparative benchmark of medical Vision Language Models (VLMs) evaluated on a range of clinically relevant visual and multimodal tasks. The study focuses on assessing how well...
The HIPAA Security Rule requires covered entities to implement mechanisms that record and examine activity in systems containing electronic PHI (45 CFR §164.312(b)). Generative AI Lab 7.8 adds an Audit...
Previously, we described how to deploy modern visual LLMs on Databricks environments at Deploying John Snow Labs Medical LLMs on Databricks: Three Flexible Deployment Options. Available options are flexible enough...
Visual de-identification is the process of detecting and masking protected health information (PHI) inside scanned medical documents, images, and PDFs. PHI in visual documents can appear in printed headers, stamps,...
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