Understanding what patients think about hospitals: A deep learning approach for detecting emotions in patient opinions.

Journal: Artificial intelligence in medicine
Published Date:

Abstract

INTRODUCTION: Most hospital assessment systems are based on the study of objective statistical variables as well as patient opinions on their experiences with respect to the services offered by each hospital. Nevertheless, studies have indicated that most of these assessment systems fail to detect patient emotions when they are assessing their stays in a hospital. This information is vital to understanding most of the patient reviews, which are very complex and convey several emotions per review. Therefore, this study aimed to address the problem of detecting multiple emotions from patient reviews.

Authors

  • Jesus Serrano-Guerrero
    Department of Information Technologies and Systems, Escuela Superior de Informática, University of Castilla-La Mancha, Ciudad Real, Spain. Electronic address: jesus.serrano@uclm.es.
  • Mohammad Bani-Doumi
    Department of Information Technologies and Systems, Escuela Superior de Informática, University of Castilla-La Mancha, Ciudad Real, Spain. Electronic address: mohammad.fakhri@alu.uclm.es.
  • Francisco P Romero
    Department of Information Technologies and Systems, Escuela Superior de Informática, University of Castilla-La Mancha, Ciudad Real, Spain. Electronic address: franciscop.romero@uclm.es.
  • Jose A Olivas
    Department of Information Technologies and Systems, Escuela Superior de Informática, University of Castilla-La Mancha, Ciudad Real, Spain. Electronic address: joseangel.olivas@uclm.es.