Combination of conditional random field with a rule based method in the extraction of PICO elements.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: Extracting primary care information in terms of Patient/Problem, Intervention, Comparison and Outcome, known as PICO elements, is difficult as the volume of medical information expands and the health semantics is complex to capture it from unstructured information. The combination of the machine learning methods (MLMs) with rule based methods (RBMs) could facilitate and improve the PICO extraction. This paper studies the PICO elements extraction methods. The goal is to combine the MLMs with the RBMs to extract PICO elements in medical papers to facilitate answering clinical questions formulated with the PICO framework.

Authors

  • Samir Chabou
    Computer Science and Engineering Department, Université du Québec en Outaouais, Gatineau, J8Y 3G5, Canada.
  • Michal Iglewski
    Computer Science and Engineering Department, Université du Québec en Outaouais, Gatineau, J8Y 3G5, Canada. iglewski@uqo.ca.