Condition: Polyp of Colon · Artificial Intelligence (AI) · Sponsor: Centre hospitalier de l'Université de Montréal (CHUM)
The goal of this observational study is to establish a video/image library dataset of complete endoscopy or partial colonoscopy procedures for patients with rectal cancer or inflammatory bowel disease (IBD). With this video/image library, the aims are: * to develop and validate novel AI-empowered solutions to automatically detect and report endoscopy quality metrics * to develop automated endoscopy reporting solutions, auditing, and educational tools for residents and fellows to enhance their endoscopy skills. The hypothesis is that a heterogeneous video/image library will provide: * comprehensive and robust source material to develop AI models * real-time quality feedback at the end of an endoscopy procedure.
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| Centre Hospitalier de l'Université de Montréal | Montreal, Quebec, Canada | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06822816