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Background <p>With the increased utilization of artificial intelligence (AI) tools in the operating room, we aimed to integrate real-time visual cues provided by AI (computer vision) with the Single-Port (SP) robotic platform for colorectal surgery.</p> Methods <p>A patient was selected for an end-ileostomy reversal using a Single-Port Robotic platform docked at the stoma site. Novel AI technology using deep-learning software was integrated into the robotic visual output system to identify different tissues within the abdominal cavity. Visual display of the information processed by the software was projected in real-time onto monitors and organized according to pre-selected color schemes.</p> Results <p>The AI technology accurately and precisely identified the individual tissue structures that had been determined intraoperatively appropriate to transect or preserve. The visual display of the AI software was color coded and easy to interpret, helping to aid safe dissection. The use of the SP robot allowed ease of access into the abdomen, providing an excellent range of motion in all quadrants, and successful mobilization of the necessary bowel to safely perform an anastomosis. This also took advantage of the prior stoma site, avoiding the need for additional incisions.</p> Conclusion <p>This report demonstrates the first successful integration of artificial intelligence using computer vision and deep learning software with the Single-Port Robotic platform to perform colorectal surgery. The technical feasibilities of these combined modalities illustrate their potential for future use in an expanded role for gastrointestinal surgery.</p>

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The first reported case using real-time artificial intelligence with single-port robotics for colorectal surgery

  • 期刊论文

  • 发表日期：

    2026年3月16日

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  • Richard Fortunato,
  • Heitham Wady,
  • Selim Gebran,
  • James T. McCormick

摘要

Background

With the increased utilization of artificial intelligence (AI) tools in the operating room, we aimed to integrate real-time visual cues provided by AI (computer vision) with the Single-Port (SP) robotic platform for colorectal surgery.

Methods

A patient was selected for an end-ileostomy reversal using a Single-Port Robotic platform docked at the stoma site. Novel AI technology using deep-learning software was integrated into the robotic visual output system to identify different tissues within the abdominal cavity. Visual display of the information processed by the software was projected in real-time onto monitors and organized according to pre-selected color schemes.

Results

The AI technology accurately and precisely identified the individual tissue structures that had been determined intraoperatively appropriate to transect or preserve. The visual display of the AI software was color coded and easy to interpret, helping to aid safe dissection. The use of the SP robot allowed ease of access into the abdomen, providing an excellent range of motion in all quadrants, and successful mobilization of the necessary bowel to safely perform an anastomosis. This also took advantage of the prior stoma site, avoiding the need for additional incisions.

Conclusion

This report demonstrates the first successful integration of artificial intelligence using computer vision and deep learning software with the Single-Port Robotic platform to perform colorectal surgery. The technical feasibilities of these combined modalities illustrate their potential for future use in an expanded role for gastrointestinal surgery.