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Inflammatory Bowel Disease V: Surgical Management01:21

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Here are some common surgical interventions for IBD:
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Artificial intelligence in gastrointestinal surgery: A systematic review.

Burak Tasci1, Sengul Dogan2, Turker Tuncer2

  • 1Vocational School of Technical Sciences, Firat University, Elazig 23119, Türkiye. btasci@firat.edu.tr.

World Journal of Gastrointestinal Surgery
|September 15, 2025
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Summary

Artificial intelligence (AI) is revolutionizing gastrointestinal (GI) surgery, enhancing patient care from planning to recovery. AI tools now often surpass human performance, but require validation for widespread clinical use.

Keywords:
Artificial intelligenceConvolutional neural networksGastrointestinal surgeryRandom forestsReinforcement learningRisk predictionSupport vector machines

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Area of Science:

  • Surgical Innovation
  • Medical Technology
  • Gastrointestinal Surgery

Background:

  • Artificial intelligence (AI) is increasingly adopted in surgery, especially gastrointestinal (GI) surgery.
  • AI offers potential to improve decision-making, accuracy, and patient outcomes throughout the surgical process.

Purpose of the Study:

  • To systematically review AI applications in GI surgery.
  • To evaluate AI's role in preoperative planning, intraoperative guidance, postoperative monitoring, diagnosis, and education.

Main Methods:

  • Systematic review following PRISMA guidelines.
  • Searched Web of Science for "artificial intelligence" AND "gastrointestinal surgery" until March 31, 2025.
  • Included 45 full-text articles reporting quantitative AI performance metrics in GI surgery.

Main Results:

  • AI demonstrated superior performance in risk prediction, lesion detection, and complication forecasting compared to traditional tools.
  • Common AI models include convolutional neural networks and reinforcement learning.
  • AI improved diagnostic accuracy, safety, documentation, and educational feedback, despite limitations in validation and explainability.

Conclusions:

  • AI is transforming all stages of GI surgery, from risk assessment to postoperative care and training.
  • AI tools frequently match or exceed expert performance.
  • Clinical adoption necessitates transparent, validated AI models integrated into surgical workflows.