Towards event sequence representation, reasoning and visualization for EHR data

  • Tao C
  • Wongsuphasawat K
  • Clark K
 et al. 
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Efficient analysis of event sequences and the ability to answer time-related, clinically important questions can accelerate clinical research in several areas such as causality assessments, decision support systems, and retrospective studies. The Clinical Narrative Temporal Reasoning Ontology (CNTRO)-based system is designed for semantically representing, annotating, and inferring temporal relations and constraints for clincial events in Electronic Health Records (EHR) represented in both structured and unstructured ways. The LifeFlow system is designed to support an interactive exploration of event sequences using visualization techniques. The combination of the two systems will provide a comprehensive environment for users to visualize inferred temporal relationships from EHR data. This paper discusses our preliminary efforts on connecting the two systems and the benefits we envision from such an environment.

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  • Cui Tao

  • Krist Wongsuphasawat

  • Kimberly Clark

  • Catherine Plaisant

  • Ben Shneiderman

  • Christopher G. Chute

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