DescriptionFor the diagnosis, prognosis, and treatment of patients, clinicians need to search and synthesize accurate, succinct, updated, and trustworthy information, from a broad set of medical literature sources (e.g., medical textbooks, journals, and synoptic overviews). In this talk, we present the research and development on a focused clinical search application that is powered by the Elsevier Healthcare Knowledge Graph. The knowledge graph platform captures and represents medical knowledge about diseases, drugs, findings, and cohorts. This medical knowledge is of high velocity, variety, volume, and veracity, and is extracted and integrated from several heterogeneous healthcare sources. We will show the benefits of combining this large scale healthcare knowledge graph with domain-specific graph analytics and machine learning methods for the purpose of focused clinical query intent interpretation and information retrieval. We will end the talk with some of the lessons learnt during our journey of taking the healthcare knowledge graph-powered focused clinical search application from an early prototype to the integration within the Elsevier ClinicalKey Search Engine, where it is being used by clinicians globally to search synoptic medical literature for point of care information.
|Period||May 6 2022|
|Event title||The Knowledge Graph Conference|
|Location||Ithaca, United States, New York|
|Degree of Recognition||International|