Current state of science in machine learning methods for automatic infant pain evaluation using facial expression information: study protocol of a systematic review and meta-analysis.

Journal: BMJ open
Published Date:

Abstract

INTRODUCTION: Infants can experience pain similar to adults, and improperly controlled pain stimuli could have a long-term adverse impact on their cognitive and neurological function development. The biggest challenge of achieving good infant pain control is obtaining objective pain assessment when direct communication is lacking. For years, computer scientists have developed many different facial expression-centred machine learning (ML) methods for automatic infant pain assessment. Many of these ML algorithms showed rather satisfactory performance and have demonstrated good potential to be further enhanced for implementation in real-world clinical settings. To date, there is no prior research that has systematically summarised and compared the performance of these ML algorithms. Our proposed meta-analysis will provide the first comprehensive evidence on this topic to guide further ML algorithm development and clinical implementation.

Authors

  • Dan Cheng
    Massachusetts General Hospital, Boston, MA.
  • Dianbo Liu
    Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge.
  • Lisa Liang Philpotts
    Treadwell Library, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Dana P Turner
    Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Timothy T Houle
    Massachusetts General Hospital, Boston, MA.
  • Lucy Chen
    Massachusetts General Hospital, Boston, MA.
  • Miaomiao Zhang
    Department of Engineering, University of Virginia, Charlottesville, Virginia, USA.
  • Jianjun Yang
    Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
  • 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.