Every day, healthcare organizations face an impossible balancing act. Clinical teams need AI tools to extract insights from unstructured medical records, validate de-identification results, and accelerate annotation workflows. But every...
TL;DR: Working with clinical text usually means solving two problems at the same time: protecting patient privacy and keeping the information that actually matters. This article walks through new tools that...
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...
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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