Use of an artificial intelligence-based rule extraction approach to predict an emergency cesarean section.

Journal: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Published Date:

Abstract

OBJECTIVE: One of the major problems with artificial intelligence (AI) is that it is generally known as a "black box". Therefore, the present study aimed to construct an emergency cesarean section (CS) prediction system using an AI-based rule extraction approach as a "white box" to detect the cause for the emergency CS.

Authors

  • Yoko Nagayasu
    Department of Obstetrics and Gynecology, Osaka Medical College, Takatsuki, Japan.
  • Daisuke Fujita
    Department of Obstetrics and Gynecology, Osaka Medical College, Takatsuki, Japan.
  • Masahide Ohmichi
    Department of Obstetrics and Gynecology, Osaka Medical College, Takatsuki, Japan.
  • Yoichi Hayashi
    Department of Computer Science, Meiji University, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan.