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Wision AI Applies Expertise in Machine-Learning and Mathematical Medicine to Improve Polyp Detection During Colonoscopy

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Data Published in Nature Biomedical Engineering Demonstrate Potential of Novel Algorithm to Improve Accuracy and Effectiveness of Diagnostic Imaging

Shanghai Wision AI Co., Ltd, a leader in developing computer-aided diagnostic algorithms and systems to improve the accuracy and effectiveness of diagnostic imaging, announced results of a study validating a novel machine-learning algorithm that improves detection of adenomatous polyps during colonoscopy. Researchers at Wision AI conducted the study in collaboration with clinicians at the Center for Advanced Endoscopy at Beth Israel Deaconess Medical Center (BIDMC), Harvard Medical School and the Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, and the results appear in the current issue of Nature Biomedical Engineering. Built on the same network architecture used to develop self-driving cars, the Wision AI algorithm is designed to enable “self-driving” in colonoscopy procedures.

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“Previous studies have shown that every one percent increase in the rate of detecting precancerous polyps results in a three percent decrease in the risk of interval colon cancer,” said Tyler Berzin, MD, Co-Director, GI Endoscopy, and Director, Advanced Endoscopy Fellowship at BIDMC and Assistant Professor of Medicine at Harvard Medical School. “This underscores the importance of accurate polyp detection. The encouraging results obtained using Wision AI demonstrate that a novel deep-learning algorithm can automatically detect polyps during colonoscopy, opening new doors to increasing the effectiveness of screening colonoscopy and enabling a new quality control metric that may improve endoscopy skills.”

“Every one percent increase in the rate of detecting precancerous polyps results in a three percent decrease in the risk of interval colon cancer,” said Tyler Berzin, MD, Co-Director, GI Endoscopy.

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Detecting and removing precancerous polyps during colonoscopy is the gold standard in preventing colon cancer, a leading cause of cancer death. However, the adenoma miss rate among the more than 14 million colonoscopies performed in the United States each year is 6 – 27 percent. The inability to recognize polyps within the visual field is a key reason that precancerous polyps go undetected. Studies show that having a second set of eyes on the monitor during colonoscopy procedures can increase detection rates by up to 30 percent. The Wision AI algorithm can serve as this second view by highlighting polyps directly on the monitor.

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