Machine learning methods for automatic pain assessment using facial expression information: Protocol for a systematic review and meta-analysis.

Journal: Medicine
Published Date:

Abstract

INTRODUCTION: Prediction of pain using machine learning algorithms is an emerging field in both computer science and clinical medicine. Several machine algorithms were developed and validated in recent years. However, the majority of studies in this topic was published on bioinformatics or computer science journals instead of medical journals. This tendency and preference led to a gap of knowledge and acknowledgment between computer scientists who invent the algorithm and medical researchers who may use the algorithms in practice. As a consequence, some of these prediction papers did not discuss the clinical utility aspects and were causally reported without following related professional guidelines (e.g., TRIPOD statement). The aim of this protocol is to systematically summarize the current evidences about performance and utility of different machine learning methods used for automatic pain assessments based on human facial expression. In addition, this study is aimed to demonstrate and fill the knowledge gap to promote interdisciplinary collaboration.

Authors

  • Dianbo Liu
    Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge.
  • Dan Cheng
    Massachusetts General Hospital, Boston, MA.
  • Timothy T Houle
    Massachusetts General Hospital, Boston, MA.
  • Lucy Chen
    Massachusetts General Hospital, Boston, MA.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Hao Deng
    Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.