Discover how John Snow Labs enables secure, scalable DICOM de-identification using AWS HealthImaging and SageMaker. [embed]https://www.youtube.com/watch?v=ubfwki4J8UA[/embed] What is the most secure way to de-identify DICOM files in AWS? To share...
As healthcare organizations increasingly rely on unstructured data like clinical notes, pathology reports, and discharge summaries, de-identifying patient information becomes mission-critical. Whether for research, AI training, or compliance, healthcare providers...
In today’s hyper-connected world, every organization is a data company, whether they realize it or not. From hospitals and banks to startups and SaaS platforms, sensitive data flows through every...
Introduction In the evolving landscape of artificial intelligence for healthcare, John Snow Labs continues to demonstrate exceptional leadership with the release of the very first Medical Vision-Language Model (VLM). This model,...
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...
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