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Large Language Models Blog

Implement Human-in-the-loop Workflows to build Regulatory-Grade AI Faster on a No-Code, Enterprise-Grade platform

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Generative AI Lab 7.2.0 introduces native LLM evaluation capabilities, enabling complete end-to-end workflows for importing prompts, generating responses via external providers (OpenAI, Azure OpenAI, Amazon SageMaker), and collecting human feedback...

The Challenges of Regulatory-Grade De-Identification at Scale  Healthcare organizations face a critical dilemma: vast volumes of patient data: free-text notes, structured fields, clinical images, even audio/video are invaluable for research,...

Converting free-text medical descriptions into structured ontology codes with validation Human phenotypes, observable traits and clinical abnormalities like “short stature” or “muscle weakness” are crucial in diagnosing diseases, especially in...

Why is it hard to use clinical guidelines during patient care?  Clinical guidelines are foundational to evidence-based care, yet their length and complexity often make them impractical to consult during...

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...
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