Automatic surgical skill assessment using a task classification model in laparoscopic sigmoidectomy.

Journal: Surgical endoscopy
Published Date: Aug 8, 2025

Abstract

BACKGROUND: In surgery, the dissection-exposure time ratio indicates surgery efficiency and relates to surgical proficiency in laparoscopic colorectal cancer surgery. This study aimed to develop an artificial intelligence (AI) model that automatically recognizes dissection and exposure times to explore surgical skill assessment.

Authors

  • Keisuke Obuchi
    Department of Surgery Hakodate Municipal Hospital Hakodate Japan.
  • Shin Takenaka
    Department for the Promotion of Medical Device Innovation, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
  • Daichi Kitaguchi
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa-City, Chiba, 277-8577, Japan.
  • Kei Nakajima
    Surgical Device Innovation.
  • Yuto Ishikawa
    Surgical Device Innovation Office, National Cancer Center Hospital East, Kashiwa, Chiba, Japan.
  • Hiroki Mitarai
    Surgical Device Innovation Office, National Cancer Center Hospital East, 6‑5‑1, Kashiwanoha, Kashiwa‑City, Chiba, 277‑8577, Japan.
  • Kyoko Ryu
    Surgical Device Innovation, National Cancer Center Hospital East, Chiba, Japan.
  • Nobuyoshi Takeshita
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa-City, Chiba, 277-8577, Japan. ntakeshi@east.ncc.go.jp.
  • Akinobu Taketomi
    Department of Gastroenterological Surgery I Graduate School of Medicine Hokkaido University Sapporo Japan.
  • Masaaki Ito
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, 277-8577, Japan.

Keywords

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