Using the Health NER Model model can save time and resources in the extraction of SDoH entities from clinical text. It also can be used for SDoH data analytics to analyze the relationship between SDoH and health outcomes.
The social determinants of health (SDoH) are the non-medical factors that influence health outcomes and usually one of the hardest type of entities to extract with pre-trained clinical NLP models....
Voice of Patients (VoP) NER, a brand-new Named Entity Recognition (NER) model released by John Snow Labs, can extract clinical entities from patient forums much better than any other clinical...
De-Identification is a process that needs to be applied to de-identify (anonymize) or obfuscate (replace with fake entities) PHI (protected health information) data from clinical notes. Obfuscation of PHI entities...
RxNorm provides normalized names for clinical drugs and links its names to many of the drug vocabularies commonly used in pharmacy management and drug interaction software. Entity Resolver pipeline in...
Recent advances in natural language processing (#NLP) caused an explosion of practical use cases that have now become viable. This webinar for #healthcare & #lifesciences leaders surveys common NLP applications...
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