Unlock hidden care gaps and maximize ROI with AI-powered patient journey analytics. Learn how integrating clinical and unstructured data identifies missed diagnoses, reduces readmissions, and streamlines coordinated care
Why analyze patient journey data? Patient journey data offers a holistic view of an individual’s healthcare experience, connecting clinical, behavioral, and operational touchpoints across time. When analyzed with AI, this...
What is a medical reasoning engine and how does it differ from search? Medical reasoning engines, powered by advanced large language models (LLMs), represent a new generation of clinical decision...
Oncology has always depended on multidisciplinary tumor boards (MTBs) to interpret complex, multimodal data, such as pathology reports, radiology findings, genomic profiles, prior treatments, patient history, and synthesize this information...
TL;DR: Working with clinical text usually means solving two problems at the same time: protecting patient privacy and keeping the information that actually matters. This article walks through new tools that...
Efficiently anonymize PHI directly within Cursor, VS Code, and Claude Code using the new Model Context Protocol integration in Healthcare NLP 6.3.0. TL;DR: John Snow Labs Healthcare NLP Release 6.3.0...
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