Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence.

Journal: Surgical endoscopy
PMID: 38760565

Abstract

BACKGROUND: Most intraoperative adverse events (iAEs) result from surgeons' errors, and bleeding is the majority of iAEs. Recognizing active bleeding timely is important to ensure safe surgery, and artificial intelligence (AI) has great potential for detecting active bleeding and providing real-time surgical support. This study aimed to develop a real-time AI model to detect active intraoperative bleeding.

Authors

  • Kenta Horita
    Department of Surgery, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Koya Hida
    Department of Surgery, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan. hidakoya@kuhp.kyoto-u.ac.jp.
  • Yoshiro Itatani
    Department of Gastrointestinal Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Haruku Fujita
    Department of Surgery, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Yu Hidaka
    Department of Biomedical Statistics and Bioinformatics, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Goshiro Yamamoto
    Kyoto University Hospital, Kyoto-City, Kyoto, Japan.
  • Masaaki Ito
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, 277-8577, Japan.
  • Kazutaka Obama
    Department of Gastroenterological Surgery, Kyoto University, Kyoto, Japan.

Keywords

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