Technology companies now market artificial intelligence services that claim to improve patient communication. Most of these products rely on large language models (LLMs) combined with basic Retrieval Augmented Generation. They can write easy-to-read educational notes and send them quickly. Yet these broad systems still miss the mark
Julia sat quietly, holding a printed brochure about diabetes care while her doctor talked through the usual tips she had heard many times before. At sixty-five, newly widowed and living...
Why the NLP Summit is now the Applied AI Summit Five years ago, we launched the NLP Summit with a simple mission: create a home for practitioners working on natural...
Introduction Oncology data is inherently complex, dispersed, and often unstructured. Extracting actionable insights from Electronic Health Records (EHRs) and other clinical data sources poses a significant challenge for healthcare professionals....
Over the past few years, there’s been a quiet revolution in healthcare AI. The buzz around large language models (LLMs) has pushed them into the limelight, capturing imaginations with their...
In today’s data-rich healthcare landscape, oncology remains among the most complex and information-dense domains. Electronic health records (EHRs), pathology reports, radiology narratives, and clinical trial documents contain vital insights about...
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