A Healthcare Knowledge Graph-based Approach to Enable Focused Clinical Search

For the diagnosis, prognosis, and treatment of their patients, clinicians need to search and synthesize accurate, succinct, updated, and trustworthy information, from a broad set of medical literature sources (e.g., patient guidelines, medical textbooks, journals, and synoptic overviews). Advanced technological solutions, which enable search and retrieval of the right excerpts from a corpus of trusted medical literature sources in the right context for clinical questions, are critical for the practice of medicine and patient care. In this talk, we present our research and development on a focused clinical search service that is powered by the Elsevier Healthcare Knowledge Graph, a knowledge platform that is composed of knowledge and data from heterogeneous healthcare sources about diseases, drugs, findings, guidelines, cohorts, journals, and books. The search service parses focused clinical search queries using different features of the healthcare knowledge graph and retrieves relevant, updated, and trusted medical content excerpts from a diverse corpus of medical literature sources. We demonstrate the importance of a scalable healthcare knowledge graph ecosystem and the use of machine learning and knowledge representation methods for focused clinical search.