A NLP Pipeline for the Automatic Extraction of Microorganisms Names from Microbiological Notes.

Journal: Studies in health technology and informatics
Published Date:

Abstract

According to the "Istituto Superiore di Sanita'" (ISS), hospital infections are the most frequent and serious complication of health care. This constitutes a real health emergency which requires incisive and joint action at all levels of the local and national health organization. Most of the valuable information related to the presence of a specific microorganism in the blood are written into the notes field of the laboratory exams results. The main objective of this work is to build a Natural Language Processing (NLP) pipeline for the automatic extraction of the names of microorganisms present in the clinical texts. A sample of 499 microbiological notes have been analysed with the developed system and all the microorganisms names have been extracted correctly, according to the labels given by the expert.

Authors

  • Sara Mora
    Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Italy.
  • Jacopo Attene
    Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Italy.
  • Roberta Gazzarata
    Healthropy, Corso Italia 15/6, 17100 Savona, Italy.
  • Giustino Parruti
    Department of Infectious Disease, Azienda Sanitaria Locale (AUSL) di Pescara, Pescara, Italy.
  • Mauro Giacomini
    DIBRIS, University of Genoa, Genoa, Italy.