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Implementation of a System for Intelligent Summarization of Longitudinal Clinical Records

  • Ayelet Goldstein
  • Yuval Shahar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8268)

Abstract

Physicians are required to interpret, abstract and present in free-text large amounts of clinical data in their daily tasks. This is especially true for chronic-disease domains, but also in other clinical domains. In our previous work, we have suggested a general framework for performing this task, given a time-oriented clinical database, and appropriate formal abstraction and summarization knowledge. We have recently developed a prototype system, CliniText, which demonstrates our ideas. Our prototype combines knowledge-based temporal data abstraction, textual summarization, abduction, and natural-language generation techniques, to generate an intelligent textual summary of longitudinal clinical data. We demonstrate both our methodology, and the feasibility of providing a free-text summary of longitudinal electronic patient records, by generating a discharge summary of a patient from the MIMIC database, who had undergone a Coronary Artery Bypass Graft operation.

Keywords

Discharge Summary Final Text Nasal Cannula Abductive Reasoning Natural Language Generation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ayelet Goldstein
    • 1
  • Yuval Shahar
    • 1
  1. 1.Ben Gurion University of the NegevBeer-ShevaIsrael

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