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Knowledge graphs have proven themselves as a robust tool in clinical applications to aid patient care and help identify treatments for new diseases. They have impacted many information retrieval systems in healthcare. In this study, we construct a disease knowledge graph using Neo4j (a knowledge graph tool) for a disease database to answer complex questions that are time-consuming and labour-intensive to be answered in the previous system. We demonstrate that new information can be inferred in a knowledge graph based on existing semantic relationships between the medical concepts and the ability to perform reasoning in the knowledge graph.
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