Grasso, ClareJoshi, AnupamSiegel, Eliot2018-10-312018-10-312016-03-24Clare Grasso, Anupam Joshi, and Eliot Siegel, Visualization of Pain Severity Events Using Semantic Structures, 2016 IEEE Tenth International Conference on Semantic Computing (ICSC) , DOI: 10.1109/ICSC.2016.5310.1109/ICSC.2016.53http://hdl.handle.net/11603/1180610th International Conference on Semantic ComputingPhysicians are often required to make critical medical decisions that may be based on previous events in the patient's health history. However, these events may be very difficult to locate in the patient record due to the large volume of unstructured textual data in the patient's chart. Even when the chart is housed in an electronic health record (EHR) system, keyword search within the chart may produce many results that are not relevant or that may overlook related expressions and concepts entirely. In addition, some medical events, such as the occurrence of symptoms, are associated with important attributes such as location or severity, and require other elements such as the type of clinical note and its date and time in order to provide the proper context of the event. This paper describes a prototype system that performs ontology-based semantic search through clinical text to extract pain severity events, and then presents them in a visualization to monitor the progression of pain over time.4 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.© 2016 IEEEsemantic searchontologyclinical decision supporthealth informaticsUMBC Ebiquity Research GroupEHR systemvisualizationclinical decision supportsemantic structurepatient careText