Skip to main content
Article thumbnail
Location of Repository

System Architecture for Temporal Information Extraction, Representation and Reasoning in Clinical Narrative Reports

By Li Zhou, Carol Friedman, Simon Parsons and George Hripcsak


Exploring temporal information in narrative Electronic Medical Records (EMRs) is essential and challenging. We propose an architecture for an integrated approach to process temporal information in clinical narrative reports. The goal is to initiate and build a foundation that supports applications which assist healthcare practice and research by including the ability to determine the time of clinical events (e.g., past vs. present). Key components include: (1) a temporal constraint structure for temporal expressions and the development of an associated tagger; (2) a Natural Language Processing (NLP) system for encoding and extracting medical events and associating them with formalized temporal data; (3) a post-processor, with a knowledge-based subsystem to help discover implicit information, that resolves temporal expressions and deals with issues such as granularity and vagueness; and (4) a reasoning mechanism which models clinical reports as Simple Temporal Problems (STPs)

Topics: Article
Publisher: American Medical Informatics Association
OAI identifier:
Provided by: PubMed Central
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://www.pubmedcentral.nih.g... (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.