Introducing computer-aided detection to the endoscopy suite

Glissen_headshot Post written by Jeremy R. Glissen Brown, MD, from the Center for Advanced Endoscopy, Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

In this issue of VideoGIE, we are excited to present a video primer that outlines a computer-aided detection (CADe) system that we have applied prospectively during screening and surveillance colonoscopies at Beth Israel Deaconess Medical Center.

We are at an unprecedented crossroads where multiple CADe technologies have already shown great promise in detecting colon polyps and high-quality prospective clinical trials are already beginning to report data on the impact of CADe on adenoma detection.

We hope that our initial experience with CADe during colonoscopy illustrates several important points, including set-up considerations, the importance of maintaining good mucosal inspection techniques, and the importance of developing familiarity with the output of the deep learning algorithm itself. GI endoscopists will need to familiarize themselves with how AI systems will be incorporated into the endoscopy suite, and we believe that CADe systems for colon polyp detection represent the starting point for this process.

Read the full article online.

The information presented in Endoscopedia reflects the opinions of the authors and does not represent the position of the American Society for Gastrointestinal Endoscopy (ASGE). ASGE expressly disclaims any warranties or guarantees, expressed or implied, and is not liable for damages of any kind in connection with the material, information, or procedures set forth.

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