Generic AI bots miss patient context. Healthcare NLP paired with medical LLMs extracts SDOH, diagnoses, and medications to deliver truly personalized patient communication.
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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