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AI in Healthcare Blog

Implement Human-in-the-loop LLM 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,...

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...

For a more in-depth exploration of AWS Health Imaging De-identification, including expanded technical details, best practices, and real-world healthcare applications, see our updated and comprehensive article: AWS Health Imaging De-identification....

What is the purpose of integrating medical LLMs for patient journeys? Integrating Document Understanding, Reasoning, and Conversational Medical LLMs (Large Language Models) enables healthcare organizations to construct longitudinal, context-rich patient...