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Clin Colon Rectal Surg
DOI: 10.1055/a-2769-1052
Review Article

The Role of Perioperative Artificial Intelligence in Colon and Rectal Surgery

Autor*innen

  • Kevin A. Chen

    1   Department of Colon and Rectal Surgery, Digestive Disease Institute, Cleveland Clinic, Cleveland, Ohio, United States

  • Shah Feroz

    1   Department of Colon and Rectal Surgery, Digestive Disease Institute, Cleveland Clinic, Cleveland, Ohio, United States

  • Stefan D. Holubar

    1   Department of Colon and Rectal Surgery, Digestive Disease Institute, Cleveland Clinic, Cleveland, Ohio, United States

Funding Information While this work was not directly supported by any funding, we would like to acknowledge support from the Cleveland Clinic Digestive Disease Institute Chief's Innovation and Research Award (grant number DDICIRA033) and the Cleveland Clinic Catalyst Grant for our ongoing AI-based projects.
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Abstract

Artificial intelligence (AI) is rapidly transforming surgical practice with growing applications in colon and rectal surgery. This review explores perioperative AI tools that assist with operative planning, intraoperative guidance, and outcome optimization. Preoperative innovations include machine learning models that outperform traditional risk calculators for predicting complications and readmissions, as well as computer vision and radiomics for analyzing imaging in colorectal cancer and inflammatory bowel disease. The integration of molecular and multiomics data further enhances personalized, precision surgical planning. Intraoperatively, deep learning enables computational identification of critical anatomy, including vascular structures, ureters, and pelvic nerves, and supports the objective analysis of advanced imaging techniques such as indocyanine green fluorescence. In terms of surgical techniques, AI-driven video analysis facilitates surgical phase recognition and automated skill assessment, whereas emerging vision–language models and surgical foundation models promise improved documentation and context-aware guidance. Future directions include generative AI for simulation, AI-based coaching, and progress toward autonomous surgical robotics. Although research remains in the early stages and is not yet ready for widespread clinical implementation, ongoing work within the field of colorectal surgery underscores the potential of AI to augment decision-making and standardize surgical care.

Keywords

artificial intelligence - machine learning - deep learning - computer vision - radiomics - semantic segmentation - surgical phase recognition - automated skill assessment - vision–language models - generative artificial intelligence

Declaration of GenAI Use

Generative AI was not used to write any part of this work. During the preparation of this work, the author used PaperPal to proofread the final version for grammar and punctuation. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the publication's content.




Publikationsverlauf

Artikel online veröffentlicht:
31. Dezember 2025

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