Healthcare NLP's de-identification MCP server lets Cursor and VS Code Copilot mask 32 PHI entity types in clinical text, with the pipeline on your servers.
Testing a clinical NLP pipeline with an AI coding agent used to mean leaving the IDE to strip PHI from notes with a separate script. The Healthcare NLP de-identification MCP...
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...
In our previous article, JSL Vision: State-of-the-Art Document Understanding on Your Hardware, we benchmarked JSL Vision against leading open-source vision-language models on FUNSD and OmniOCR In this follow-up, we address...
Tl; DR: This post explains why specialized pretrained PHI pipelines are often the best starting point for data scientists working with clinical text. Instead of building a custom PHI system...
TL; DR This post presents a focused update on large-scale clinical de-identification benchmarks, emphasizing pipeline design, execution strategy, and infrastructure-aware performance. Rather than treating accuracy as an isolated metric, we...
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