Aiworks Cholangioscopy
Computer-assisted detection device used with a standard endoscope for identifying polyps and adenomas in the colon. This device can be used during real-time colonoscopy procedures or in pre-recorded videos.
Each time it identifies a polyp, it highlights the area within a bounding box, providing the confidence score and emitting a beep. The software performs detection at an average of 30 frames per second, taking screenshots of the observed lesions during the procedure for review at any other time. - Real-time AI second opinion on areas of interest - Improved cost-effectiveness through appropriate sample acquisition with AI assistance.
Diagnosing malignancy in indeterminate biliary strictures is a challenge. Endoscopic retrograde cholangiopancreatography (ERCP) is the most used procedure to evaluate the biliary system; however, it has low diagnostic accuracy and imaging limitations. Various malignancy classifications (Monaco, Carlos Robles-Medranda et al., and Mendoza classification) have been proposed. However, even among experts, there is interobserver variability in detecting available neoplastic lesions. To overcome the diagnostic accuracy limitations of ERCP, the Ecuadorian Institute of Digestive Diseases (IECED; Guayaquil, Ecuador), a reputed center for gastroenterology and endoscopy, in collaboration with mdconsgroup (Guayaquil, Ecuador), a well-established software company in Guayaquil, Ecuador.
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Benefits Of Aiworks Cholangioscopy
Computer-Assisted Detection
Aiworks Cholangioscopy is a computer-assisted detection device used with a standard endoscope for identifying areas suggestive of neoplasia in the bile duct.
Real-Time or Pre-Recorded Cholangioscopy
This device can be used during real-time cholangioscopy procedures or in pre-recorded videos.
Highlighted Areas and Confidence Score
Each time it identifies a lesion, it highlights the area within a bounding box, providing the confidence score and emitting a beep.
Detection at 30 Frames Per Second
The software performs detection at an average of 30 frames per second, taking screenshots of the observed lesions during the procedure for review at any other time.