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The purpose of this study is to develop and validate a deep learning algorithm to realize automatic recognition of colonic segments under conventional colonoscopy. Then, evaluate the accuracy this new artificial intelligence(AI) assisted recognition system in clinic practice.
Colonoscopy is recommended as a routine examination for colorectal cancer screening. Complete inspection of all colon segments is the basis of colonoscopy quality control, and furthermore improves the detection rates of small adenomas. Recently, deep learning algorithm based on central neural networks (CNN) has shown multiple potential in computer-aided detection and computer-aided diagnose of gastrointestinal lesions. However, there is still a blank in recognition of anatomic sites, which restricts the realization of AI-aided lesions detection and disease severity scoring. This study aim to train an algorithm to recognize key colonic segments, and testify the accuracy of each segments recognition as compared to endoscopic physicians.
AI assisted recognition of colonic segments
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Published on BioPortfolio: 2019-09-18T03:27:46-0400
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Chronic or recurrent colonic disorders without an identifiable structural or biochemical explanation. The widely recognized IRRITABLE BOWEL SYNDROME falls into this category.
Inflammation of the COLONIC DIVERTICULA, generally with abscess formation and subsequent perforation.
Functional obstruction of the COLON leading to MEGACOLON in the absence of obvious COLONIC DISEASES or mechanical obstruction. When this condition is acquired, acute, and coexisting with another medical condition (trauma, surgery, serious injuries or illness, or medication), it is called Ogilvie's syndrome.
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Pathological processes in the COLON region of the large intestine (INTESTINE, LARGE).
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