NLP for Clinical IE

AIME 2017 Tutorial: Natural Language Processing for Clinical Information Extraction

21 June 2017

This tutorial will focus on a high-level introduction to NLP applied to clinical text. It will include a presentation of NLP and information extraction, characteristics of clinical text, existing NLP tools applied to clinical text, an overview of clinical NLP projects preparation and tools evaluation, and hands-on exercises with NLP tools to illustrate the theory presented. This tutorial addresses the need in the community to learn through hands-on experience how to apply and experiment with NLP tools that are publicly available.

A set of de-identified clinical documents will be used to illustrate the process of implementing an NLP tool. The documents will be described along with the target concepts that will be extracted.

Aims: At the end of this tutorial, participants will be able to

  • Identify and explain the characteristics of clinical text
  • Distinguish the various methods used to extract information from clinical text
  • Compare these information extraction methods, existing tools, and terminological resources
  • Benefit from hands-on experience with a selection of NLP tools adapted to clinical text

Content details


Stéphane Meystre

Medical University of South Carolina, Charleston, SC, USA

Meliha Yetisgen

University of Washington, Seattle, WA, USA

Scott DuVall

University of Utah & Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA

Hua Xu

University of Texas Health Science Center, Houston, TX, USA