A technological convergence in hepatobiliary oncology: Evolving roles of smart surgical systems.

Journal: Bioscience trends
Published Date:

Abstract

Cancer remains a major threat to human health, with the incidence of hepatobiliary tumors consistently high. Treatment methods for hepatobiliary tumors include surgical intervention, ablation, embolization, and pharmacological treatments, with surgery being a critical component of systemic treatment for patients with hepatobiliary tumors. Compared to other methods, surgery is the most effective way to remove tumors and improve survival rates, serving as the cornerstone of various treatment strategies. However, the large patient population sometimes burdens traditional surgical oncology. In recent years, rapidly advancing artificial intelligence (AI) technologies, characterized by efficiency, precision, and personalization, align well with the treatment philosophy of oncologic surgery. Increasing studies have shown that AI-assisted surgical oncology outperforms traditional approaches in many aspects. This review, based on machine learning, neural networks, and other AI techniques, discusses the various applications of AI throughout the entire process of hepatobiliary tumor surgical treatment, including diagnostic assistance, surgical decision-making, intraoperative support, postoperative monitoring, risk assessment, and medical education. It offers new insights and directions for the integration and application of AI in oncologic surgery.

Authors

  • Xuanci Bai
    Department of Clinical Medicine, Shanghai Medical College, Fudan University, Shanghai, China.
  • Runze Huang
    Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716-2150, USA.
  • Qinyu Liu
    Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
  • Xin Jin
    Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
  • Lu Wang
    Department of Laboratory, Akesu Center of Disease Control and Prevention, Akesu, China.
  • Wei Tang
    Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Kenji Karako
    Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Weiping Zhu
    State Key Laboratory of Bioreactor Engineering, Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, PR China.

Keywords

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