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Creating a Clinical Knowledge Graph with Spark NLP and Neo4j – Webinar

The knowledge graph represents a collection of connected entities and their relations. A knowledge graph that is fueled by machine learning utilizes natural language processing to construct a comprehensive and semantic view of the entities. A complete knowledge graph allows answering and search systems to retrieve answers to given queries. In this study, we built a knowledge graph using Spark NLP models and Neo4j. The marriage of Spark NLP and Neo4j is very promising for creating clinical knowledge graphs to do a deeper analysis, Q&A tasks, and get insights.

Can Natural Language Processing Help Alleviate Physician Burnout?

Clinicians are under time pressure due to increasing demand for medical care, information overload, and administrative regulations.  A study conducted by Mayo...