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New Artificial Intelligence System Can Detect Bowel Cancer - TechSource International - Leaders in Technology News

New Artificial Intelligence system can detect Bowel Cancer in less than a second

The Japanese system was found to have a 94 percent accuracy rate.
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Scientists in Japan have claimed bowel cancer can be detected in less than a second, thanks to the new artificial intelligence (AI) system software.

Scientists from Showa University in Yokohama, Japan developed the computer-aided diagnostic system that uses an endocytoscopic image – a 500-fold magnified view of a colorectal polyp – to analyse about 300 features of the polyp after applying narrow-band imaging (NBI) mode or staining with methylene blue.

The system compares the features of each polyp against more than 30,000 endocytoscopic images that were used for machine learning, allowing it to predict the lesion pathology in less than a second.

While presenting the results of the study at United European Gastroenterology Week in Barcelona, Spain, Dr Yuichi Mori, study leader from Showa University in Yokohama, Japan, said, "The most remarkable breakthrough with this system is that AI enables real-time optical biopsy of colorectal polyps during colonoscopy, regardless of the endoscopists' skill.”

Mori indicated that the system could eventually spare many patients from needless surgery, albeit it is yet to receive the regulatory approval. “This is thought to decrease the risk of colorectal cancer and, ultimately, cancer-related death,” and “allows the complete resection of adenomatous (cancerous) polyps and prevents unnecessary polypectomy (removal) of non-neoplastic polyps," Mori said. "We believe these results are acceptable for clinical application and our immediate goal is to obtain regulatory approval for the diagnostic system."

The AI-assisted system was used to predict the pathology of each polyp and those predictions were compared with the pathological report obtained from the final resected specimens. The team assessed 306 polyps in real-time by using the AI-assisted system, providing a sensitivity of 94 per cent, specificity of 79 per cent, accuracy of 86 per cent, and positive and negative predictive values of 79 per cent and 93 per cent respectively, in identifying neoplastic changes.

The team is now undertaking a multi-centre study for this purpose and are also working on developing an automatic polyp detection system.