Indication model for laparoscopic repeat liver resection in the era of artificial intelligence: machine learning prediction of surgical indication.

Journal: HPB : the official journal of the International Hepato Pancreato Biliary Association
Published Date:

Abstract

BACKGROUND: Laparoscopic repeat liver resection (LRLR) is still a challenging technique and requires a careful selection of indications. However, the current difficulty scoring system is not suitable for selecting indications. The purpose of this study is to develop the indication model for LRLR using machine learning and to identify factors associated with open conversion (OC).

Authors

  • Sung Jun Jo
    Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
  • Jinsoo Rhu
    Department of Surgery.
  • Jongman Kim
  • Gyu-Seong Choi
    Department of Surgery.
  • Jae-Won Joh
    Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.