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Creating a Clinical Knowledge Graph with Spark NLP and neo4j

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.

Empowering Spark NLP for underrepresented languages

As in many fields of science, the vast majority of AI and NLP research and tools are developed in English; and other...