Artificial intelligence in colorectal surgery: an AI-powered systematic review.

Journal: Techniques in coloproctology
Published Date:

Abstract

Artificial intelligence (AI) has the potential to revolutionize surgery in the coming years. Still, it is essential to clarify what the meaningful current applications are and what can be reasonably expected. This AI-powered review assessed the role of AI in colorectal surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic search of PubMed, Embase, Scopus, Cochrane Library databases, and gray literature was conducted on all available articles on AI in colorectal surgery (from January 1 1997 to March 1 2021), aiming to define the perioperative applications of AI. Potentially eligible studies were identified using novel software powered by natural language processing (NLP) and machine learning (ML) technologies dedicated to systematic reviews. Out of 1238 articles identified, 115 were included in the final analysis. Available articles addressed the role of AI in several areas of interest. In the preoperative phase, AI can be used to define tailored treatment algorithms, support clinical decision-making, assess the risk of complications, and predict surgical outcomes and survival. Intraoperatively, AI-enhanced surgery and integration of AI in robotic platforms have been suggested. After surgery, AI can be implemented in the Enhanced Recovery after Surgery (ERAS) pathway. Additional areas of applications included the assessment of patient-reported outcomes, automated pathology assessment, and research. Available data on these aspects are limited, and AI in colorectal surgery is still in its infancy. However, the rapid evolution of technologies makes it likely that it will increasingly be incorporated into everyday practice.

Authors

  • A Spinelli
    Department of Biomedical Sciences, Humanitas University, Rozzano Milano, Italy‬‬‬‬‬‬‬‬.
  • F M Carrano
    IRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, MI, Italy.
  • M E Laino
    Artificial Intelligence Center, Humanitas Clinical and Research Center-IRCCS, Via A. Manzoni 56, 20089, Rozzano, MI, Italy.
  • M Andreozzi
    Department of Clinical Medicine and Surgery, University "Federico II" of Naples, Naples, Italy.
  • G Koleth
    Department of Gastroenterology and Hepatology, Hospital Selayang, Selangor, Malaysia.
  • C Hassan
    IRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, MI, Italy.
  • A Repici
    IRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, MI, Italy.
  • M Chand
    Division of Surgery and Interventional Sciences, Gastrointestinal Services Department, University College London, University College London Hospitals NHS Foundation Trust, London, UK. m.chand@ucl.ac.uk.
  • V Savevski
    Artificial Intelligence Center, Humanitas Clinical and Research Center-IRCCS, Via A. Manzoni 56, 20089, Rozzano, MI, Italy.
  • G Pellino
    Colorectal Surgery Unit, University Hospital Vall d'Hebron, Autonomous University of Barcelona, Barcelona, Spain.