Searching and Analyzing Unstructured and Structured Data at Scale with MetiStream Ember and Elastic

In this video, we show you how MetiStream Ember and Elastic can be used together to empower users with the ability to easily search and analyze structured and unstructured healthcare data, like doctors' notes, which have traditionally posed challenges to healthcare organizations' analytics efforts. Using the MIMIC III dataset, we'll demonstrate how Ember's clinical NLP engine can be used to extract clinical concepts and terms from unstructured text in multi-year backlogs at scale to fill in gaps in structured data and provide a fuller view of reality. Once processed, data is opened up for intuitive search by clinical ontologies such as ICD 9 / 10, SNOMED, CPT, LOINC, and RxNorm, surfacing insights many times faster and more consistently than manual chart review can support.

Michael Mulcahy

Nathan Salmon

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