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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.

About the speaker

Ali Emre Varol
Data scientist

Ali Emre Varol is a data scientist working on Spark NLP for Healthcare at John Snow Labs with a decade of industry experience. He has previously worked as a software engineer to develop ERP solutions and led teams and projects building machine learning solutions in a variety of industries. He is also pursuing his Ph.D. in Industrial Engineering at Middle East Technical University and holds an MS degree in Industrial Engineering.