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In what could mark a major leap in cancer detection by artificial intelligence, researchers at Showa University in Yokohama, Japan, have developed an AI software that they claim can spot bowel cancer in less than a second.

In a recently conducted trial, the AI system was successfully able to pinpoint potentially dangerous tumours from endoscopy images with clinical accuracy.

Led by Dr. Yuichi Mori, the study involved 250 men and women in whom colorectal polyps had been detected using endocytoscopy. In total 306 polyps were assessed, and scientists used the AI program to predict the pathology of each polyp. The predictions were then compared with the final pathological report, and it was found that the system correctly detected 94% of cancers by matching each growth against over 30,000 images that were used for machine learning. What is remarkable is that it took the program less than a second to review each magnified endoscopic image and determine whether or not the polyp was malignant.

“The most remarkable breakthrough with this system is that artificial intelligence enables real-time optical biopsy of colorectal polyps during colonoscopy, regardless of the endoscopists’ skill,” Mori said.

While the diagnostic system is yet to obtain the regulatory approval, Mori believes it could really help patients do away with needless surgeries. “This allows the complete resection of adenomatous (cancerous) polyps and prevents unnecessary polypectomy (removal) of non-neoplastic polyps,” he said.

The findings were also presented at the ongoing United European Gastroenterology (UEG) Week in Barcelona, Spain.

The research team is now working full throttle on this project, and they plan to take the study to a new level by developing an automatic polyp detection system. “Precise on-site identification of adenomas during colonoscopy contributes to the complete resection of neoplastic lesions” Mori added. “This is thought to decrease the risk of colorectal cancer and, ultimately, cancer-related death.”

Writes and reports on lnformation Technology. Full stack on artificial intelligence, data science, and music.


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